Subsurface energy and environmental systems like geothermal energy systems, geological carbon storage, underground hydrogen storage, groundwater flow systems, etc., play a vital role for mitigating climate change and achieving net-zero. At the same time, their complex, heterogeneous, multiscale, and uncertain nature presents major challenges for modelling, prediction, monitoring, and decision-making, particularly in multiphysics and multiscale model coupling, data integration, and real-time monitoring and control.
Artificial intelligence (AI) and scientific machine learning (SciML) are creating new opportunities to address these challenges. This session aims to bring together researchers from geoscience, hydrology, subsurface energy, computational science, and AI to discuss recent advances at the interface between these fields. We invite contributions on the development and application of AI and SciML methods for subsurface energy and environmental systems. Topics include, but are not limited to, physics-informed machine learning, neural operators, reduced-order modelling, surrogate and generative modelling, multimodal data fusion, digital twins, explainable and trustworthy AI, large language models, and agentic AI.
The session will provide a platform for interdisciplinary exchange on emerging methods, practical applications, current limitations, and future research directions.

The rapid development of pretrained models, including large language and foundation models, opens up many new applications in geosciences. Fine tuning or deploying existing models directly to geoscience problems gives us all the benefits of very large models, trained with vast data sets, whilst reducing the compute cost and required specialist data sets, compared to older deep learning techniques. The potential cost and energy saving, and scientific power of these models can revolutionise AI in geosciences. In this session, we look forward to seeing state-of-the-art fine tuning techniques specialized for geoscience; novel deployment of pretrained models of any sort; and lessons learnt from trial and error. We would love to see applications across the geosciences, from geophysics to education, remote sensing to hands on field applications.

Artificial intelligence (AI) is currently transforming data analysis and modelling of the Earth system. While statistical and data-driven models have been used for a long time, recent advances now allow for encoding non-linear, spatio-temporal relationships robustly without sacrificing interpretability. This has the potential to accelerate climate science by providing new physics-based modelling approaches; improving our understanding of the underlying processes; reducing and better quantifying climate signals, variability, and uncertainty; and even making predictions directly from observations across different spatio-temporal scales. We encourage participants to discuss the limitations of AI methods (including their often substantial training-data requirements, susceptibility to data leakage, poor generalisation, and physical inconsistencies) to help ensure that these methods are applied where they are fit for purpose and add value.


This session aims to provide a venue to present the latest progress in the use of AI applied to all aspects of climate science and we welcome abstracts focussed on, but not limited to:
- Causal discovery and inference: causal impact assessment, interventions, counterfactual analysis
- Learning processes, equations, and feature representations across models and observations
- Hybrid physics-AI and differentiable models, climate model emulators, data-model integration
- AI-based detection and attribution approaches, including for extreme events
- Probabilistic modelling and uncertainty quantification
- AI-based climate downscaling, including super-resolution and bias-correction
- Climate model analysis in the AI era, including benchmarking and stress-testing
- Explainable AI applications to climate data science and climate modelling
- Distributional robustness and transfer learning, including out-of-distribution generalisation tasks
- AI reasoning and agent-based workflows for analysing climate data, developing, improving, testing, and porting scientific code, and climate information

Machine learning (ML) methods have emerged as powerful tools to tackle various challenges in ocean science, encompassing physical oceanography, biogeochemistry, and sea ice research.
This session aims to explore the application of ML methods in ocean science, with a focus on advancing our understanding and addressing key challenges in the field. Our objective is to foster discussions, share recent advancements, and explore future directions in the field of ML methods for ocean science.
A wide range of machine learning techniques can be considered including supervised or unsupervised learning, interpretable techniques, and physics-informed and generative models. The applications to be addressed span both observational and modelling approaches.

Observational approaches include for example:
- Identifying patterns and features in oceanic fields
- Filling observational gaps of in-situ or satellite observations
- Inferring unobserved variables or unobserved scales
- Automating quality control of data

Modelling approaches can address (but are not restricted to):
- Designing new parameterization schemes in ocean models
- Emulating partially or completely ocean models
- Parameter tuning and model uncertainty
- Agentic AI

The session also welcomes submissions at the interface between modelling and observations, such as data assimilation, data-model fusion, or bias correction.

Researchers and practitioners working in the domain of ocean science, as well as those interested in the application of ML methods, are encouraged to attend and participate in this session.

This session explores how assured, trustworthy use of AI for geospatial data can support decision-making and implementation strategies. The use of AI-enabled geospatial tools is increasing, spanning site suitability, climate resilience, risk management and investment decisions. Across all of these applications, questions of data provenance, model assurance, confidence levels and uncertainty analysis of the AI systems themselves become critical to responsible deployment.

We invite contributions on: methods for validating geospatial AI models and the datasets used; approaches to closing evidence gaps in data-poor areas; and frameworks to measure confidence and uncertainty in AI-derived geospatial outputs. We particularly welcome interdisciplinary contributions, including case studies that demonstrate how responsible GeoAI approaches can support fair access and devolution.

A robotic platform maps outdoor nitrogen dioxide, moves indoors and concludes that an anomaly warrants returning tomorrow. A drone communicates with a ground robot in a dense forest, profiling structure under and above the canopy. An edge device runs simulates multiple scenarios through pre-trained emulators of a regional system. Every component of both exists. The system that ties them together could be next.
Environmental science is being transformed by automated platforms, new low power sensing, digital twins, foundation models and agentic AI. Almost all of it is designed to improve how we measure and simulate the environment, or how we assist a human analyst. A challenging problem is the decision layer: how a system forms a meaningful hypothesis about the environment in front of it, whether real or digital, re-plans what and where to sample or simulate as evidence accumulates, quantifies its own uncertainty well enough to act on it, and knows when to proceed, escalate to a human, or defer. Without all combined, autonomy in the geosciences remains a sophisticated remote control. But when is enough, and who decides? In this session we welcome all contributions on systems that plan, execute or adapt in the geosciences. This can include:
- bespoke and LLM-powered agents with tool use over instruments and models
- software that makes such systems buildable: orchestration frameworks, control interfaces, benchmarks, testbeds and digital twins for training and evaluation
- instrument, sensor and platform development for autonomous operation, with its power, communications and field-hardening constraints
- adaptive, information-driven sampling and autonomous re-tasking of observing networks
machine-generated hypotheses and how they are validated
- closed-loop experimentation controlling instrumentation and iterating on results
- real-time uncertainty quantification and provenance
- accounts of real deployments, including failures
- oversight, escalation protocols, evidential standards and levels-of-autonomy frameworks, including what regulators require before acting on autonomously generated evidence.

Work at any level of maturity is welcome, from deployed systems to position papers, and from all career stages.

Recent advances in Large Language Models (LLMs), Natural Language Processing (NLP), multimodal AI, and AI agents are rapidly changing geosciences research. These technologies offer new opportunities for knowledge discovery, data analysis, evidence synthesis, and real-time monitoring. At the same time, the rapid growth of digital archives, from scientific literature and news articles to social media and historical documents or photographs, offers opportunities to explore new data sources in geosciences research.
This session examines how geoscientists are using LLMs, NLP, AI agents and text-as-data approaches across hydrology, climate, natural hazards, and the broader earth system sciences research fields. We invite contributions that develop or apply such methods to extract, organize, and interpret information from unstructured data sources; address methodological challenges such as uncertainty, bias, and validation; or integrate text and image mining approaches into geoscientific workflows.
We particularly welcome submissions on topics including, but not limited to:
- Text and image-based analysis of geoscientific data, e.g. assessment of natural hazard impacts and real-time disaster monitoring.
- Chatbots and AI agents in geosciences
- Evidence synthesis and literature mapping
- Public sentiment and perception analysis
- Policy tracking and narrative analysis
- Social media analyses
- Enhancement of metadata and data descriptions
- AI agents for automated or semi-automated geoscientific workflows
- Integration of LLMs with remote sensing or image data
- Methodological challenges in using LLMs and NLP-based analyses, including bias, reproducibility, and interpretability

By sharing case studies, technical developments, and lessons learned, we aim to promote the effective use of these tools while also highlighting the challenges that newcomers may encounter, including issues with data coverage, quality control, and reproducibility concerns. By sharing best practices, this session aims to inspire collaboration and innovation in harnessing LLMs, NLP, and text-as-data in geosciences.

Causal inference provides a powerful framework for unraveling cause-effect relationships, disentangling complex processes within Earth system sciences and quantifying causal effects by combining domain knowledge, machine learning (ML) models, and data from observations and climate model simulations. Learning causal relationships from Earth system data across different timescales is crucial for understanding its complex emergent dynamics and validating climate models, which we count on to simulate future changes. A better understanding of the Earth system helps us design more effective mitigation and adaptation strategies to address open risks with environmental and societal relevance. This session welcomes contributions that highlight innovative approaches, methodologies, and case studies employing causality across Earth sciences. The overall aim is to foster interdisciplinary discussions, encourage collaborations, and promote the development of robust analysis frameworks. We would like to initiate discussions on experiences, challenges, and future development of causal methodologies in Earth system sciences.

The topics of interest for this session include, but are not limited to:
• Causal discovery and inference: algorithms and methods for uncovering causal networks among Earth system processes (e.g., weather, climate, clouds and aerosols, teleconnections, chemical-dynamical interactions);
• Causal effect estimation: statistical techniques to estimate causal effects of anthropogenic or natural forcings in the Earth system;
• Case studies investigating causal pathways and mechanisms driving natural and anthropogenic perturbations such as climate change, land-ocean interactions, teleconnections, extreme events, volcanic eruptions, wildfires, etc.;
• Causal modelling, network analysis, and causal model evaluation: development and application of causal models, network analysis, and graphical models to capture the intricate interconnections and feedbacks within dynamical systems;
• Integration of causal discovery with deep learning (DL) as a promising avenue for improving climate simulations;
• Merging of explainable and causal Artificial Intelligence (AI): discovering governing equations, parameterizations, and relationships based on climate data;
• Challenges and limitations: difficulties associated with the application of causal inference, such as data preprocessing, violations of assumptions, or uncertainty quantification.

Deep learning is causing a major paradigm shift in weather forecasting from physical modelling to data-driven or hybrid approaches. While the first ML-systems are now used in operational medium-range weather forecasting, the adaptation of deep learning techniques to the subseasonal-to-seasonal (S2S), decadal and multidecadal range is still lagging behind. New approaches are needed for S2S since atmospheric initial conditions are no longer the main driver of predictability. Similarly, deep-learning approaches are emerging for the decadal and multidecadal timescales, when climate forcing becomes a dominant influence on the atmosphere. The scarcity of simulation data and the lack of ground truth pose serious challenges at these time ranges. For this session, we solicit abstracts that present current ideas and results at the intersection of deep learning, S2S-forecasting and climate emulation and simulation.

In particular, we welcome contributions from the following areas.
- Generative modelling for time-scales beyond medium-range
- Calibration and uncertainty estimation for data-driven long-term forecasting
- Coupled generative models of earth system components
- Predictability limits and failure modes in data-driven long-term forecasting
- Out-of distribution emulation and forecasting
- Benchmarking and validation of long-term forecasts with data-driven models
- Identification of drivers of increased predictability and forecast skill for data-driven models (XAI)

Monitoring carbon and greenhouse gas exchange between atmosphere, land, ocean and human systems underpins the Global Stocktake, national inventories, carbon markets and carbon dioxide removal (CDR). Yet bottom-up (inventories, process-based and data-driven models), top-down (atmospheric inversions) and bookkeeping (land-use change) estimates remain uncertain and often disagree, while the credibility of measurement, reporting and verification (MRV) rests on independent methods agreeing. Machine learning (ML) offers new ways to enhance, complement, emulate, integrate or even replace established observational, modelling and analytical workflows.

This session invites contributions using ML to advance carbon cycle monitoring and understanding across all compartments (atmosphere, vegetation, soils, permafrost, wetlands, inland waters, coastal and open ocean, anthropogenic sources) and all relevant trace gases, including CO2, CH4, N2O, CO, COS and isotopes. We welcome the full breadth of ML: foundation models, transformers, GNNs, CNNs, generative models (diffusion, flow matching), hybrid and differentiable modelling, Bayesian ML, symbolic regression, interpretable, robust and trustworthy ML, and tabular methods such as gradient-boosted trees. We particularly encourage work bridging science, policy and industry.
Topics include, but are not limited to:

- ML-enhanced bottom-up estimates: upscaling, mapping stocks and fluxes, inventories
- ML for top-down inversions: transport emulators, data assimilation, retrievals, point-source detection
- ML for bookkeeping and land-use change emissions
- Emulators and foundation models for process-based and Earth system models
- Hybrid modelling, and generative models for gap-filling, downscaling and ensemble generation
- Fusion of remote sensing with in-situ data (eddy covariance, flask networks, ocean pCO2)
- ML for carbon cycle process understanding and discovery: drivers, feedbacks and emergent constraints, with explainability, causality and uncertainty quantification
- Reconciling lines of evidence across methods, compartments and gases
- Monitoring for policy and industry: MRV, national inventories, carbon markets, CDR verification
- ML-based decision support and policy pathways (reinforcement learning, integrated assessment models)
- Benchmarks, datasets & open tools

In geoscientific applications, we observe a steady increase in the amount of data and in model complexity. This development is partly driven by technological advances that provide access to higher-resolution data, greater computational capabilities, and increasingly complex coupled numerical models. However, these advances also yield major challenges, since the resulting data amount and the number of model evaluations required are becoming infeasible with traditional evaluation methods.
Therefore, many applications take advantage of scientific machine learning (SciML) approaches to overcome these challenges. However, the rapid development of new methods within this field highlights one fundamental challenge: existing benchmarks typically do not adequately represent the complexity, diversity, and requirements of real-case geoscientific applications. Many commonly used benchmarks rely on relatively simple datasets, assume idealized problem setting and are defined for narrow tasks only. This makes it difficult to assess advances in SciML for their transferability and performance for a broader range of geoscientific applications.
To bridge this gap, this session welcomes contributions presenting complex, realistic benchmarks that enable the validation of scientific machine learning approaches for both numerical modelling and scientific data analysis. We particularly encourage benchmarks that capture current challenges such as: large and heterogeneous datasets, high-dimensional features in terms of the spatial-temporal relationships and the parameter space, multi-scale and complex coupled physical processes, limited or noisy observations, and the need for computationally efficient, resource-aware benchmark designs that enable model training and evaluation under limited computational budgets. We encourage submission from different geoscientific disciplines as benchmark requirements can differ significantly across the domains. At the same time, we welcome contributions from the application side that illustrate limitations of existing benchmarks and discuss which characteristics need to be preserved and represented by SciML methods to be beneficial in the given application context.
The session aims to bring together researchers developing SciML methods, benchmarks, and domain-specific applications. By connecting these perspectives, we seek to identify current gaps in benchmarking practices.

European seas and coastal areas are facing and are projected to face growing pressures from climate change, sea-level rise, storm surges, extreme waves, coastal flooding and erosion, marine heatwaves, changing sea-ice conditions and ecosystem degradation. Addressing these challenges requires integrated approaches that combine observations with ocean, climate, wave, biogeochemical and ecosystem models, high-resolution coastal simulations, artificial intelligence, and social and economic information.
This inter- and transdisciplinary session will explore how Ocean Digital Twins can bring these different sources of knowledge on future seasonal, decadal, and centennial ocean hazards together and turn model results into practical climate and ocean services. We invite contributions on advanced modeling; seasonal-to-decadal predictions and climate projections; model coupling and uncertainty; high-performance computing; AI-based/emulator-based predictions[AM1.1][AM1.2]; early warning; and interactive applications linked to European infrastructures such as EDITO and Destination Earth.
Applications may include future coastal flooding and erosion, compound hazards, coastal cities and ports, offshore wind and other marine renewable-energy systems, fisheries and aquaculture, marine ecosystems, biodiversity, sea ice and safe navigation. We also welcome research on adaptation pathways, nature-based solutions, vulnerability and resilience assessment, and environmental, social and economic trade-offs.
The session aims to bring together oceanographers, climate scientists, coastal engineers, ecologists, computer and data scientists, social scientists, practitioners and decision-makers. Participatory research involving public authorities, civil-protection agencies, port and energy operators, fisheries and aquaculture stakeholders, NGOs and coastal communities is also welcome.
The session is jointly organized by four Horizon Europe projects—MOIRAI, SEACLIM, EU-INTERCHANGE and RIVIERADE—which address complementary aspects of ocean and climate modelling, coastal risks, the land–river–ocean continuum, as well as, digital tools and services for climate adaptation.

Over the last two decades, OpenStreetMap (OSM) has evolved into a global, community-generated source of spatio-temporal geodata. Volunteers continuously document infrastructure, land use, transportation networks, environmental features and other spatial entities that are often not covered in comparable detail or at the same temporal resolution by national mapping agencies. This global grassroots mapping effort creates a continuously evolving record of changes in geographical space, reflecting processes such as urban growth, agricultural transformation, natural hazards and disasters, and the spatial impacts of global environmental change.

OSM data are increasingly combined with governmental topographic data, research datasets and remote sensing observations to support research and generate new insights across the geosciences. However, the long-term preservation and scientific reuse of this evolving data commons raises important challenges. These include the preservation of spatio-temporal versions, FAIR access, persistent scientific citation, provenance documentation, reproducibility and cartographic reuse.

This session invites contributions addressing the use, preservation and scientific exploitation of OpenStreetMap as a spatio-temporal data commons. We particularly welcome use cases, methodological approaches and lessons learned from different branches of the geosciences, as well as contributions discussing challenges and opportunities for long-term preservation, provenance, FAIR principles, citation, reproducibility and integration with other geospatial data sources.

Downscaling aims to process and refine global climate model output to provide information at spatial and temporal scales suitable for impact studies. In response to the current challenges posed by climate change and variability, downscaling techniques continue to play an important role in the development of new services and products. While the refinement of downscaling techniques proceeds at an unprecedented pace, users of climate information are facing the novel challenge of how to select amongst the choice of available datasets or how to assess their credibility with respect to a particular application. In this context, model evaluation and verification is growing in relevance and advances in the field will likely require close collaboration between various disciplines.

Recent developments, including the integration of AI and machine learning applications, the emergence of kilometre-scale simulations, and the widespread availability of open-source downscaling products, add new dimensions to this challenge. These advances raise important questions about the ‘added value’ of downscaling, especially in light of the cascade of uncertainty and the need for robust evaluation frameworks.

In our session, we aim to bring together scientists from the various geoscientific disciplines interrelated through downscaling: atmospheric modeling, climate change impact modeling, machine learning and verification research. We also invite philosophers of climate science to stimulate our discussion about the novel challenges that arise from evaluating complex models and modelling chains in the face of the increasingly heterogeneous needs of the growing user communities.

Contributions to this session may address, but are not limited to:
- newly available downscaling products,
- applications relying on downscaled data and impact assessments,
- downscaling method development and machine learning,
- bias correction and statistical postprocessing,
- challenges in the data management of kilometer-scale simulations,
- verification, uncertainty quantification and the added value of downscaling,
- downscaling approaches in light of computational epistemology.

Digital geoscience depends on combining Earth observations, in situ measurements, model output, and digital twins across domains and scales. Yet differences in grids, data formats, computing environments, and access conditions can make results difficult to compare and reproduce.
This session explores how open, interoperable workflows can bridge these gaps. The Pangeo community and its open-source ecosystem support scalable analysis from laptops to HPC and cloud systems. A unified, standardized data infrastructure based on Discrete Global Grid Systems (DGGS) could provide a common spatial framework for Earth observations and model outputs that currently use heterogeneous grids. Combined with cloud-native formats, such a framework can reduce repeated, ad hoc data transformations and make their provenance easier to trace. This creates opportunities for analysis-ready data and reproducible, trustworthy AI, while enabling tests of computational efficiency. Earth system digital twins and federated data platforms offer settings to test integration of observations, simulations, and user applications across domains and scales.
We welcome methodological advances and applied studies from atmosphere, climate, ocean, land, biodiversity, and natural hazards research. Topics include:
Cross-domain fusion of observations, simulations, and digital-twin outputs
DGGS-based indexing, regridding, and analysis across spatial and temporal scales
Scalable, reproducible, and FAIR workflows using open-source tools (Xarray, Iris, Dask, Jupyter, Kerchunk, VirtualiZarr, Intake) alongside open standards and formats (STAC, Zarr, Parquet, GeoParquet)
Interoperable data access and processing across HPC, cloud, and federated infrastructures
AI/ML workflows with traceable data preparation, validation, uncertainty assessment, and evaluation of computational efficiency
Executable notebooks, workflow portability, sustainable computing, and practical barriers to reuse
Contributions may focus on Pangeo, DGGS, digital twins, or their combination. Studies using Pangeo tools alone to build reproducible, FAIR, and community-driven workflows in any domain of Earth or environmental science are equally welcome. We especially encourage work that shows how a method developed in one geoscience domain can be adapted, evaluated, and reused in another.

This session addresses the challenge of consistently combining terrestrial and marine datasets referenced to different vertical reference surfaces, a fundamental requirement for, among other applications, effective coastal-zone management and robust coastal-hazard assessment. This includes the integration of terrain elevations, bathymetric data, and/or sea-level data, including model-derived water levels, as well as the realization and unification of the vertical reference surfaces to which these datasets are referenced.
We welcome contributions proposing strategies for land–sea vertical reference integration across scales, from global to local, as well as studies applying and evaluating such strategies. Contributions are also invited on the realization of height and depth reference surfaces, including (marine) geoid and chart datum models, height-system unification, and the transfer of vertical datums across the land–sea interface.

Moving to a low carbon economy to fight climate change will require the constructions and operations of multiples large renewable energy and critical mineral mining projects, which often include extensive supportive infrastructures across large geographic areas. As such, these projects will have long-lasting and far-reaching impacts on the host ecosystems, the watersheds and the communities. Across the world, these projects are more likely to be developed in rural and remote areas where biophysical systems have had limited anthropogenic impacts. These new projects will bring a suite of impacts to theses socio-ecological systems that can be hard to quantify and, therefore, mitigate. To support a green, just and equitable transition, natural and social scientists across a broad range of disciplines must come together to develop innovative cumulative assessments methods, frameworks, and indicators. This is imperative to support science-based impact assessments and policies across the globe.

In this session, we invite participant to submit their work related to natural project development, impact assessments, and large-scale modelling of cumulative impacts. We especially are interested in bringing together participants from different areas of the world to showcase their research in their particular context.

This session explores the need, challenges, opportunities, drawbacks, and obstacles in applying and explaining the special world of compositional data spaces.

Compositional data is a special type of non-negative data that carries relevant information in the ratios among the variables rather than in the actual data values. Considering the metric of compositional data may conflict with familiar geoscientific approaches: single chemical elements or mineralogical concentrations as proxies for environmental changes, counts of individuals as indicators of ecological states, etc.
Felix Chayes (1960) and John Aitchison (1981) began to establish a parallel universe of statistical methods beyond normality and linearity to gain sustainable insights into Compositional Data Analysis (CoDA) in the geosciences. Since then, the geoscientific community has expanded the range of methods.
However, even in the era of rapidly expanding big data methods, sustainable CoDA remains underrepresented in recent research.

We welcome contributions from all disciplines to answer the following questions: (i) How does CoDA transform our view of the earth? (ii) How can we gain new sustainable insights by applying CoDA? (iii) How can CodA increase the scalability of numeric models? (iv) How to deal with zeros and missing data? (vi) How to deal with low-count compositions? (v) How should we convincingly communicate CoDA?
This session addresses researchers from all quantitative fields to exchange ideas and foster interdisciplinary collaboration.

Human health risks in a changing climate: observed impacts, adaptation and future risks
Climate change is increasingly affecting population health through heat, cold, floods, droughts, wildfires, storms and rapidly changing, or compound, hazards. These events contribute not only to premature mortality but also to cardiorespiratory and infectious diseases, injuries, adverse mental health outcomes and disruption of healthcare and other essential services. An estimated 489,000 heat-related deaths occur globally each year, and more than 181,000 heat-related deaths were recorded across Europe during the summers of 2022–2024. Occupational heat exposure also affects more than 2.4 billion workers globally and is associated with nearly 23 million injuries each year.
These impacts are unevenly distributed. Socioeconomic position, age, sex and gender, ethnicity, pre-existing health conditions, occupation and place intersect to shape exposure, susceptibility and adaptive capacity. Marginalised populations, including older adults, children, people with chronic conditions, outdoor and manual workers, and communities living in low-income or geographically exposed areas, often bear a disproportionate burden. An intersectional and climate-justice perspective is therefore essential for understanding health risks and developing effective and equitable responses.
This session, organised in collaboration with the Swedish Centre for Impacts of Climate Extremes (CLIMES), invites contributions examining the diverse and unequal effects of climate variability, climate change and extreme events on human health. We particularly welcome studies that:
1. quantify observed impacts and future health risks from single, compound and cascading climate hazards;
2. investigate the attribution of health impacts to anthropogenic climate change;
3. identify intersecting socioeconomic, demographic, occupational and spatial vulnerabilities;
4. develop or evaluate health early-warning systems, impact-based forecasting and other climate services;
5. assess the effectiveness, equity and potential unintended consequences of adaptation interventions; and
6. integrate climate, environmental, health and social data to strengthen public health preparedness, resilient health systems and equitable adaptation.
7. storylines methods and their capacity to inform decision makers.
We welcome contributions using epidemiological, modelling, qualitative, participatory and interdisciplinary approaches.

Scientific assessments play a critical role in translating rapidly evolving climate research into actionable knowledge for decision-makers. From the Intergovernmental Panel on Climate Change (IPCC) to national, regional, sectoral, and local assessment efforts, assessments provide structured syntheses of evidence that help governments, communities, businesses, and civil society evaluate climate risks, identify response options, and make informed decisions under uncertainty. Assessments increasingly serve as a bridge between scientific understanding and practical action, supporting planning processes ranging from national adaptation strategies to community resilience and infrastructure investments.

At the same time, data systems have become foundational to assessment practice. The growing availability of observations, model outputs, socioeconomic datasets, and decision-support tools creates new opportunities for assessment, while also raising challenges related to transparency, traceability, accessibility, stewardship, and long-term usability. International data support activities underscore the importance of robust data infrastructure in enabling credible and policy-relevant assessments.

This session invites contributions on the development, application, and future of climate assessment activities across all scales. We welcome presentations from national and international assessment programs, regional and local assessment initiatives, Indigenous and community-led assessment efforts, and organizations that employ assessments to support planning and decision-making. Contributions addressing assessment methodologies, uncertainty communication, stakeholder engagement, knowledge synthesis, data stewardship, data rescue, emerging data products, and assessment-informed policy or practice are especially encouraged. The session will also highlight emerging initiatives, including efforts by scientific societies such as the American Geophysical Union’s Science Assessment Initiative, that seek to strengthen the global assessment ecosystem and accelerate the delivery of decision-relevant climate knowledge.

Extreme heat is a leading weather-related threat to human health, with risk projected to intensify as the climate warms. Robust and transferable estimates of heat-related health risk require an understanding of how socioeconomic and demographic contexts influence who is most vulnerable in addition to the role confounding environmental stressors such as humidity and air pollution play in exacerbating dangerous conditions. This session brings together environmental epidemiologists, data scientists, climate scientists, and human physiologists to advance methods for predicting and forecasting heat-related morbidity and mortality, and to better understand the factors that might modify risk beyond temperature.

We seek machine-learning, statistical, physiological or hybrid approaches that provide new insights into heat-related health risks and/or translate these insights into improved predictive frameworks. Emphasis is placed on novel methodologies improving the validation and transferability of models across regions, climates, and populations. We are particularly interested in approaches that address limited or heterogeneous health data to enable prediction in data-sparse settings, where populations highly vulnerable to extreme heat may be poorly represented. These include physiologically based approaches that derive limits of human heat tolerance from thermoregulation rather than from local health records, and that resolve risk across distinct population cohorts. We also welcome contributions improving predictions under anthropogenic warming, extending model transferability into different climates. Advances in our understanding of compound risks, prediction methods and model transferability can support more effective and equitable Heat-Health Warning Systems.

Climate hazards consistently expose and often intensify socioeconomic inequalities. Vulnerability to extreme events is not evenly distributed within or across societies; rather, it is shaped by existing social, economic, and political conditions. As such, inequality, defined as the uneven distribution of resources, opportunities, and power has been recognised by the United Nations and other global policy frameworks as a central factor influencing progress toward the Sustainable Development Goals (SDGs).
This session invites interdisciplinary contributions, bringing together geoscientists, social scientists, economists, and policy experts to examine the complex and often compounding interactions between social inequalities and climate hazards such as floods, heatwaves, droughts, storms, landslides, and wildfires across different scales, including within countries, between countries, and across continents.
Topics of interest include (but are not limited to):
-Case studies illustrating how environmental and social inequalities intersect.
-Types of inequality: social, gender-based, infrastructural, recovery time, education, income source, wealth distribution, climate justice, food security
-Impacts of climate hazards: displacement, fatalities, psychological and physical health, developmental setbacks.
-Long-term recovery challenges: absence of recovery, prolonged recovery periods, slower developmental trajectories.
-Historical and political-ecological perspectives on disasters and their long-term societal impacts.
-Innovations in data, metrics, or methods (e.g., AI, remote sensing, socio-environmental modelling) for assessing inequality and disaster risk across spatial and temporal scales.

Urban areas are increasingly vulnerable to severe weather events, including localized intense precipitation, extreme heat, and urban windstorms. Developing effective Early Warning Systems (EWS) that are fit for purpose requires bridging high-resolution physical science, cutting-edge AI methodologies, and actionable co-produced risk communications and policies. This requires understanding both physical forecast performance and how warnings are operationalized to drive effective anticipatory action, particularly in vulnerable urban environments.

This session, organized as part of the WMO Urban-PREDICT initiative, explores recent advances in high-resolution urban weather forecasting, multi-hazard prediction, and the interdisciplinary co-design of early warnings. We welcome contributions covering:
• High-Resolution Physical Modelling: Sub-kilometer and hectometric-scale Numerical Weather Prediction for urban environments and their application to early warning.
• AI & Machine Learning Applications: Standalone AI or physics-informed AI prediction systems, fast emulators, data-driven downscaling, and novel observational datasets (e.g., radar, crowdsourced sensors, urban IoT), including pathways for operational deployment and data accessibility.
• Impact & Hazard Modelling: Translating meteorological variables into actionable hazard metrics for urban infrastructure, energy systems, and public health, considering the consequences for community response.
• Interdisciplinary Co-Production: Frameworks and case studies linking physical hazard forecasts to societal response, policy, and community-level EWS resilience.

This session will feature contributions from ongoing research under the Urban-PREDICT framework, including international intercomparison initiatives (e.g., RUMI high-resolution modelling over Hong Kong, HEAT-X AI heat downscaling) and local case study approaches to early warning and data availability (e.g., Hong Kong, Lusaka, and Montevideo). We encourage submissions across physical meteorology, machine learning, and social sciences.

Agricultural production depends on climatic conditions such as precipitation and temperature, as well as their interactions with each other and with non-climatic factors. Disentangling these effects and understanding which climatic conditions affect agriculture, how strongly, and how future production could change under global warming is crucial for safeguarding future food production, supporting timely climate adaptation through management practices, and improving impact models and assessments. We invite submissions across a broad spectrum of approaches for assessment of climate change impacts on agriculture. Submissions may include, but are not limited to, the following themes:
1- Assessment of climatic conditions, including extremes (droughts, heatwaves) and averages, and their effect on agricultural production, variability and anomalies.
2- Assessment of adaptation practices, including but not limited to crop diversification, irrigation, and fertilization in crop production.
3- Projections of future agricultural production using multi-model climate simulations as well as single-model initial conditions and assessment of time of emergence.
4- Spatial and temporal variability and the role of teleconnections in climate risks to agriculture.
5- Supply chains, financial losses, and the role of insurance in alleviating financial losses in the agriculture sector.
6- Methodological advancements and intercomparison of process-based, statistical, and AI-based models for agricultural production and climate impact assessments.

Climate change and environmental degradation constitute a growing threat to the stability of societal and economical systems. The observed and anticipated increase in the frequency and intensity of extreme weather events under future emission scenarios, combined with the projected long-term shifts in climate patterns are already leading to significant economic damages on a local to global scale with repercussions in insurance and finance sectors.

To mitigate systemic risks from extreme weather events an improved model representation of extreme weather and climate hazards at impact relevant scales and a better understanding of their often compounding ways they cause impacts is urgently needed. In recognition of this challenge climate risk assessments for the financial and insurance sectors have experienced amplified attention in both the academic and private spheres.

This session aims at providing a platform for actors from academia and the private sector to exchange information on strategies for assessing climate risk, and is organised under three main pillars:

-Physical Climate Risks: Trends, Processes and Modelling
-Identifying and Managing Climate Risks
-Quantifying Damages and Impacts from Climate Risks

We encourage submissions on a wide range of topics including innovative climate risk modeling and model evaluation, damage functions, integrated assessment modelling, bias adjustment and downscaling methods, climate emulators, climate hazard indicators and their projections for specific sectors (e.g. food, energy, insurance, real estate, supply chains), impact data collection and categorization.

The Atlantic Meridional Overturning Circulation (AMOC) plays a critical role in regulating Earth’s climate. Therefore, a potential future weakening or even collapse of the AMOC could have major climatic and societal impacts. While some of these changes and impacts have been investigated, their wide-ranging nature has led to scattered knowledge with limited intercomparisons between different lines of evidence. In this session, we bridge multiple disciplines and bring together the latest knowledge on AMOC changes and their impacts.

We welcome all contributions that investigate changes in the AMOC and their Earth System impacts. These can include direct physical impacts, such as atmospheric, oceanic, or cryospheric; biogeochemical as well as marine and terrestrial ecosystem responses; and socioeconomic impacts, such as health, agricultural, and economic repercussions. Contributions can cover any timescale, from paleoclimate and the recent past to future projections, from seasonal and decadal changes to long-term (centennial to millennial), both past and future. In addition, the AMOC can be studied in a range of settings, from internal variability to forced trends or abrupt/tipping behaviour, affecting both mean and extreme variables.

We call for contributions employing a broad range of tools, from Earth System, regional, and simple models to reanalyses and observations/proxies, as well as socioeconomic and impact-related models. Finally, as the Atlantic subpolar gyre (SPG) is an ocean system whose strength, stability, and impact on the climate are strongly connected to the AMOC, we also welcome contributions discussing the impacts of SPG changes on the Earth System.

Considerable progress has been made in modelling multi-hazard and systemic climate and natural hazard risk, including the interactions, cascading effects, and feedbacks through which climate-related risks propagate across interconnected systems. However, stronger links are needed between these advances in risk assessment and the emerging discourses and approaches to systemic risk governance. In particular, approaches to governance need to reflect the distinctive characteristics of systemic risk while responding to diverse stakeholder perceptions, knowledge, capacities, and needs.
This interdisciplinary and transdisciplinary session aims to bridge systemic risk assessment, modelling, communication, and governance. We invite presentations and posters addressing three interconnected questions:
1. How can multi-hazard and systemic risks be assessed and communicated in ways that are scientifically robust, decision-relevant, and appropriate to the needs and perceptions of different stakeholders?
2. How do systemic risks propagate across interconnected infrastructure, economic, environmental, and social systems, and how can these dynamics, including cascading impacts, feedbacks, and potential tipping points, be simulated and assessed?
3. What science-based governance frameworks and discourses can translate systemic risk knowledge into effective climate change adaptation, disaster risk reduction, and progress towards the Sustainable Development Goals? In particular, how might systemic risk governance be organised around and combine instrumental, reflective, participatory, and epistemological governance discourses?
By bringing together perspectives from hazard risk science, modelling, governance, policy, and practice, the session seeks to advance a more integrated understanding of how knowledge about climate-related systemic risk can inform actionable and legitimate governance responses.
We will actively seek to enhance Equality, Diversity, and Inclusion (EDI) in the composition and conduct of the session.

Disturbances, such as extreme weather events, play a key role in shaping ecosystems. Under climate change, extreme weather hazards undergo changes in frequency, intensity and seasonality. While ecosystem-based adaptation and nature-based solutions are gaining traction, it is crucial to investigate the diverse interactions between extreme weather risk, ecosystems, and their services.

This session seeks to highlight research on the nexus of weather and climate related extreme events and ecosystems. We encourage submissions on: 1) investigations into the key attributes and patterns of extreme weather events which affect ecosystem composition, structure and functioning, 2) studies on how ecosystems respond to and recover from extreme weather events across past, present, and future climates, 3) Implications of extreme weather impacts on ecosystems for biodiversity and ecosystem service provision. We welcome a diverse array of contributions, including theoretical analyses, modelling approaches, field studies, experimental designs, and remote sensing analysis.

Key topics include:
- Identification of extreme weather risk hotspots, and subsequent ecosystem responses (terrestrial, coastal, or marine) in past, present and future climates

- Role of extreme weather in shaping ecosystem composition, biodiversity, structure and functioning, and its impact on ecosystems service provisions across temporal and spatial scales
Interactions of natural hazard, anthropogenic and biogenic disturbances with ecosystems (including compounding events)

- Ecosystem vulnerability, resilience and recovery dynamics under weather extremes, including regime shifts / tipping points in ecosystems
Impact and efficacy of nature-based solutions under extreme conditions, risk of maladaptation or disservices

This session aims to showcase recent research progress and augment existing knowledge in polar meteorology and climate, and the atmosphere-land ice-sea ice coupling in both Hemispheres. It will provide a setting to foster discussion and help identify gaps, tools, and studies needed to address these open questions. It is also an opportunity to convey newly acquired knowledge to the community.
We invite contributions on all observational and numerical modelling aspects of Arctic and Antarctic meteorology and climatology that address atmospheric interactions with the cryosphere. This may include but is not limited to studies on past, present and future of:
- Atmospheric processes that influence sea ice (snow on sea ice, sea ice melt, polynya formation and sea ice production and transport) and associated feedbacks,
- Surface energy balance above the snow/ice surface.
- The variability of the polar large-scale atmospheric circulation (such as polar jets, the circumpolar trough and storm tracks) and impact on the cryosphere (sea ice and land ice),
- Atmosphere-cryosphere interactions triggered by synoptic and meso-scale weather phenomena such as cold air outbreaks, katabatic winds, extratropical cyclones, polar cyclones, atmospheric rivers, Foehn winds, and heatwaves,
- Role of clouds in polar climate and impact on the land ice and sea ice through interactions with radiation,
- High-latitude dust and pollution, deposition on snow and ice, and related impacts.
- Teleconnections and climate indices and their role in land ice/sea ice variability.
Presentations including new observational (ground- and satellite-based) and modelling methodologies specific to polar regions are encouraged. Contributions related to results from recent field campaigns in Greenland, the Arctic, and in the Southern Ocean/Antarctica are most welcome.

The Mediterranean and other water-stressed regions are increasingly recognized as advanced laboratories of planetary limits, where climate change, land-system change, and biodiversity loss interact to jeopardize the interconnected Water-Energy-Food-Ecosystem-Health (WEFEH) nexus. The concept of a Safe Operating Space (SOS) for freshwaters, rooted in the planetary boundaries framework, offers a compelling lens for defining thresholds of availability, quality, and ecosystem stability beyond which irreversible damage may occur. Yet translating these thresholds into regionally adapted, policy-relevant, and operational tools remains a major scientific and governance challenge, compounded by the complexity of interlinkages among the different SOS components.

This session invites contributions that bridge the gap between global planetary boundaries and their local operationalization, from scientific frameworks and safe operating spaces at the global/regional scale, to digital tools, decision support systems, and living labs at the basin and field scale. We welcome studies on Nexus approaches (WEFE-H, Source-to-Sea) that move water governance from reactive to predictive management, leveraging digitalization, data science, and Earth observation. Contributions addressing the social and equity dimensions of these transitions, access, gender, and climate justice, alongside technical and modelling approaches, are strongly encouraged.

The session aims to bring together climate scientists, hydrologists, nexus and planetary-boundaries researchers, and practitioners to advance a shared operational agenda for water security under climate change, with a focus on the Mediterranean and other vulnerable regions worldwide.

As a result of a warming Arctic, there is an increased frequency and intensity of extreme weather events such as marine and terrestrial heatwaves, rain-on-snow events, and intense windstorms. Such extreme weather events can trigger cascading, multidisciplinary impacts across the Arctic system. This session bridges the gap between physical mechanisms and on-the-ground realities by investigating the physical drivers of extreme events within oceanic, atmospheric, and cryospheric systems, alongside their wide spectrum of impacts. These impacts range from rapid physical shifts, such as enhanced meltwater runoff, sudden sea-ice loss, and snowpack depletion, to societal and ecological disruptions, including infrastructure damage, traffic disruptions, and threats to reindeer herding and Indigenous livelihoods.
We welcome submissions based on modeling, observations, or interdisciplinary frameworks, such as those incorporating local and Indigenous knowledge systems, that investigate extreme weather phenomena, their physical drivers, and their direct and cascading impacts on the Arctic environment, ecosystems, and local communities.

This session investigates the interaction between human-made interventions in nature and social systems, and how reliance on technology is intertwined with current and future climate hazards. While technology is meant to make the environment liveable, it can also obscure exposure to climate hazards and as such increase vulnerability. We aim to discuss risks and impacts in domains such as health, ecosystems, the built environment, financial and economic systems, as well as possible risk management and resilience practices.

Reliance on technologies to create amenable conditions and expand the human climate niche may amplify risk because these technologies can fail. In addition, the increasing engineeredness of our environment creates a general sense of control and security, which reduces awareness of and preparedness for unexpected events and circumstances.

We invite contributions that explore the effects of socio-technological interactions under changing climate hazards on risk perception, risk, and impacts. Topics of interest include but are not limited to: natural hazards; compounding and systemic risks; adaptation technologies; the Anthropocene. Methods of interest include, but are not limited to: modelling; case studies; event, impact, and damage attribution; climate and adaptation storylines; interviews and participatory research; and policy analysis. Presentations from all subject areas – physical sciences, geography, social sciences, and the humanities – are welcome.

The Mediterranean is a climate change hotspot where warming and changes in the hydrological cycle are reshaping high-impact weather and climate extremes. Heatwaves, droughts, extreme precipitation and floods, wildfires, marine extremes, and compound and cascading events interact with exposure and vulnerability, generating complex environmental and societal risks.
Addressing these challenges requires connecting advances in observations, physical processes, modelling, prediction and climate projections with impact and risk assessment. Understanding exposure, vulnerability and adaptive capacity is equally essential for translating climate knowledge into effective early warning, decision-support and adaptation.
This session brings together physical and social sciences, technological developments and stakeholder perspectives to advance integrated understanding of Mediterranean extremes, their impacts and pathways to resilience.
We welcome contributions on:
• Physical processes, observations, modelling, attribution, prediction and projections of Mediterranean weather and climate extremes.
• Single, compound and cascading hazards and their interactions across spatial and temporal scales.
• Impacts, exposure, vulnerability and risk across health, water, agriculture, energy, ecosystems, infrastructure and urban areas.
• Methods integrating physical, environmental, social and economic dimensions of climate risk.
• Climate services, impact-based forecasting, early-warning systems and decision-support tools, including Earth observation, AI and digital twins.
• Adaptation and risk-reduction strategies, including nature-based solutions, and evidence of their effectiveness, limitations and trade-offs.
• Co-production of knowledge, stakeholder and citizen engagement, communication and capacity building.
We particularly encourage contributions bridging disciplines, sectors and Mediterranean regions, including approaches addressing inequalities in data, vulnerability and adaptive capacity.
Supported by the FutureMed COST Action (CA22162), this session welcomes contributions from within and beyond the network. It aims to strengthen transdisciplinary collaboration and connect climate science with societal needs, adaptation and resilience.

Extreme weather and climate events can disrupt many aspects of human societies, including physical and mental health, livelihoods, food and water service, infrastructure, and human mobility. Yet these impacts are still often assessed one hazard at a time, even though severe consequences frequently arise from interacting hazards. Compound events may involve concurrent, sequential, spatially connected, or preconditioned hazards, and their impacts can be nonlinear, cascading, and greater than the sum of impacts associated with individual hazards.

This session focuses on the impacts of compound weather and climate events on human societies. We welcome research on diverse types of compound events, including, but not limited to, heat and drought; drought followed by wildfire; extreme heat combined with wildfire; tropical cyclones accompanied or followed by extreme rainfall, flooding, and storm surge; and rapid transitions between opposing climate extremes. Contributions may examine mortality and morbidity, mental health, migration and displacement, food and water insecurity, livelihood losses and financial security, health-system burdens, infrastructure failure, conflict, and structural inequality. We particularly encourage work addressing unequal exposure, vulnerability, adaptive capacity, resilience, and recovery.

This session welcomes empirical, modelling, qualitative, participatory, and mixed-methods studies at any spatial scale. Relevant topics include definitions and metrics; detection and attribution; historical trends and future projections; evidence linking compound events to human outcomes; causal inference and uncertainty assessment; integration of climate data with administrative records, surveys, remote sensing, and community knowledge; and applications to early warning, anticipatory action, adaptation, preparedness, risk communication, and equitable risk reduction.

By bringing together climate and Earth-system science, epidemiology, public health, geography, economics, sociology, demography, engineering, disaster-risk research, and public policy and practice, the session aims to advance knowledge of how compound events are anticipated, measured, experienced, and managed.

High-impact climate and weather events typically result from the interaction of multiple climate and weather drivers, as well as vulnerability and exposure, across various spatial and temporal scales. Such compound events often cause more severe socio-economic impacts than single-hazard events, rendering traditional univariate extreme event analyses and risk assessment techniques insufficient. It is, therefore, crucial to develop new methodologies that account for the possible interaction of multiple physical and societal drivers when analyzing high-impact events under present and future conditions. This session aims to address several challenges and topics.
These include: (1) identifying the compounding drivers, including physical drivers (e.g., modes of variability) and/or drivers of vulnerability and exposure, of the most impactful events; (2) Developing methods to better shape the definition and classification of compound events, i.e. legitimate the ‘cut-offs’ in the considered number of hazard types or variables to ultimately disentangle enough information for decision-making; (3) Understanding whether and how often novel compound events, including record-shattering events, will emerge in the future; (4) Explicitly addressing and communicating uncertainties in present-day and future assessments (e.g., via climate storylines/scenarios); (5) Disentangling the contribution of climate change in recently observed events and future projections (attribution); (6) Employing novel Single Model Initial-condition Large Ensemble simulations, which provide hundreds to thousands of years of plausible weather, to better study compound events. (7) Developing novel statistical methods (e.g., machine learning, artificial intelligence, and climate model emulators) for studying compound events; (8) Assessing the weather forecast skill for compound events at different temporal scales; (9) Evaluating the performance of novel statistical methods, climate and impact models, in representing compound events and developing novel methods for constraining/reducing uncertainties (e.g., multivariate bias correction and observational constraints); and (10) engaging with stakeholders to ensure the relevance of the aforementioned analyses.
We invite presentations on all aspects of compound events, including but not limited to the topics and research challenges described above.

The impacts of weather and climate extremes depend on interactions between physical hazards, exposure, and vulnerability. Beyond intensity, the duration, timing, spatial extent, and co-occurrence of extremes can strongly influence their consequences. Understanding these relationships is essential for assessing how climate change alters risks to societies and ecosystems.
This interdisciplinary session connects research on the physical drivers of weather and climate extremes with assessments of their societal and environmental impacts. We particularly welcome studies that investigate how the mechanisms and characteristics of extremes shape their consequences, and how these relationships change under different climatic and socioeconomic conditions.
Contributions are invited on:
- Physical drivers and impact pathways: Atmospheric dynamics, ocean–atmosphere interactions, land–atmosphere coupling, and thermodynamic processes shaping extremes and their consequences. Topics include the roles of persistence, spatial extent, antecedent conditions, and compound or sequential hazards in determining impacts.
- Attribution of extremes and their consequences: Assessments of how anthropogenic climate change and natural variability influence extremes and associated impacts, including approaches that distinguish climatic influences from changes in exposure and vulnerability.
- Prediction and assessment of climate risks: Integration of observations, climate simulations, statistical approaches, and impact models to understand and anticipate risks under present and future conditions. Contributions may address cross-sector and cascading impacts, impact-based forecasting, and the implications of improved physical understanding for preparedness and adaptation.
We welcome observational, modelling, theoretical, and empirical studies addressing heatwaves, droughts, heavy precipitation, floods, fire weather, and compound extremes. Contributions may examine individual links between physical drivers, hazards, and impacts; interdisciplinary studies connecting these elements are particularly encouraged. The session aims to strengthen dialogue between extreme-event science and impact research, advancing understanding of how physical climate processes translate into societal and environmental risks.

Earth Observation (EO) offers a powerful means of monitoring changes in climate, ecosystems, and human environments at both global and local scales. These observations generate a wide array of climate and environmental variables, and they are delivered as Analysis-Ready Data (ARD). While ARD is globally accessible and scientifically robust, it might lack the specificity and contextual relevance required to effectively address local challenges. To bridge this gap, ARD must be transformed into Action-Ready Information (ARI): tailored data products and insights that support local decision-making and reflect community priorities. This transformation depends on co-creation, a collaborative process involving local communities, scientists, engineers, policymakers, and private sector stakeholders. For example, by integrating satellite EO with locally collected data from ground, water, and airborne platforms, we can enhance data granularity, validate satellite outputs, and generate customized, equitable, and actionable solutions. This session will explore how data can be harnessed to support environmental monitoring, local climate mitigation and adaptation, and sustainable development. It will emphasize the importance of identifying gaps between global datasets and local needs, and present strategies to close these gaps through innovation (e.g. new technologies and open FAIR science), inclusive engagement, and capacity building. Economic and policy dimensions will also be addressed, including the sustainability of community-led initiatives, the role of citizen science, funding mechanisms, and scalable technologies that enhance data utility for local solutions. The practical implementation challenges confronting policymakers when seeking to engage with EO data, particularly in the context of constrained policy capacities, will also be discussed. We invite participants from across/around the EO ecosystem: researchers in both physical and social sciences, community leaders, and stakeholders from policy and business sectors. We do not limit us only to satellite EO. We do consider non-EO observations and data, and their applications. We will share case studies, identify synergies between global and local efforts, and co-create knowledge that informs both local action and global strategies. By synthesizing diverse experiences, this session aims to advance EO as a tool for addressing the interconnected climate and environmental challenges we face locally and globally.

Extreme events such as tropical cyclones, heatwaves, and earthquakes threaten populations worldwide. Climate change is increasing the frequency and intensity of many natural hazards, which can interact with community exposure, inequalities, and vulnerabilities to cause substantial harm. These harms include forced migration, health and wellbeing effects, and other societal impacts. A growing literature at the intersection of the natural and social sciences examines the impacts of extreme events on populations, as well as people’s behavioral, attitudinal, and emotional responses.

Understanding the diverse societal impacts of natural hazards requires approaches that connect knowledge across disciplines, scales, and sectors. Yet, the challenges of doing so remain underexplored. Challenges include methodological choices, scales of analysis (e.g., regional, national), and means of translating scientific outputs into actionable information for policy and practice. This session provides a platform for contributions that bridge disciplines and sectors to better understand societal impacts of, and responses to, extreme events and related compound hazards.

We invite contributions including, but not limited to, studies of:
- Challenges for interdisciplinary and cross-sectoral collaborations
- Migration, displacement, and immobility due to extreme events
- Health and wellbeing effects of climate change and extreme events
- Food production and security in relation to extreme weather
- The interplay between climate change, environment, and conflict
- Environmental attitudes and behaviors influenced by extreme events

Social-science and humanities (SSH) research is crucial for informing ambitious, effective, just and societally acceptable climate action. This session highlights how SSH insights on social metabolism, labor transitions, perceptions and societal readiness, institutional dynamics, justice, needs and capabilities, and power relations can enrich and reshape diverse modeling approaches. We aim to provide a platform for interdisciplinary work that broadens what models and scenarios can represent, clarifies their limits, and strengthens connections across methods and disciplines.
We welcome contributions that:
integrate SSH concepts and methods into integrated assessment models (IAMs), energy–economy–environment models, energy-system models, or other analytical frameworks;
use empirical, qualitative or participatory approaches to inform model assumptions, structures, constraints and scenario design;
engage with normative dimensions such as fairness, feasibility, responsibility and societal acceptance, including in emerging areas such as carbon dioxide removal and other climate-response strategies;
connect justice questions to marginalized or disadvantaged communities, particularly in the Global South;
examine how governance, institutions, finance, law, power relations, and material and human needs shape transition pathways;
investigate social outcomes of modeled scenarios, including distributional, labor, health and wellbeing implications; and
explore how new data, methods and technologies can address, or reproduce, gaps in whose experiences and priorities are represented in climate analysis.
We particularly encourage work engaging with distributive, procedural, recognitional, transitional and other dimensions of justice, as well as studies that provide meaningful two-way connections between social science and modeling communities. Contributions need not themselves be modeling studies where they provide empirical, conceptual or normative insights that can inform how climate and energy scenarios are developed, evaluated or interpreted.
By convening these perspectives, the session seeks to advance interdisciplinary approaches that make climate and energy modeling more relevant, inclusive and transparent about both what it represents and what lies beyond its scope.

Cities are intricate multi-scale systems, composed of diverse sub-components such as population, energy, transport, and climate. These components interact on various time scales, from hourly to seasonal to annual and beyond. Effective urban models and digital twins, crucial for urban planning and policy-making, must account for these complex interactions as they govern the growth and functioning of cities, often giving rise to emergent large-scale phenomena. However, our ability to quantitatively describe city behaviour remains limited due to the myriad of processes, scales, and feedbacks involved.

This session invites studies focused on modelling and monitoring the dynamics of multiple sectors and city-biosphere interactions. Topics of interest include, but are not limited to:
- Demography
- Urban transport networks
- Energy consumption
- Anthropogenic emissions and pollution
- Urban climate
- Urban hydrology
- Urban ecology

Our aim is to elucidate the complex dynamics within urban environments and explore how urban form and function can be optimised to enhance the liveability and well-being of their citizens.

Recent years have seen an increasing number of armed conflicts worldwide, both within and between states. Beyond their devastating humanitarian consequences, armed conflicts and associated military activities can have profound and long-lasting environmental impacts. These impacts include, but are not limited to, land-use and land-cover change, ecosystem degradation, biodiversity loss, soil and water contamination, disruptions to food production systems, increased climate vulnerability, and greenhouse gas emissions, with consequences that may extend from local to global scales.

This session welcomes empirical studies investigating the environmental dimensions of armed conflict across spatial and temporal scales. This means global as well as place-based analyses are suitable. We encourage contributions that employ a range of methods and data sources, including remote sensing, geospatial analysis, machine learning, artificial intelligence, field observations, environmental monitoring, and integrated modelling approaches.

We particularly welcome conflict-engaged research, in which armed conflict is treated not merely as contextual background but as an explicit analytical component. We seek studies that directly examine the relationships between conflict dynamics, military activities (also outside of direct war contexts), and observed environmental changes, advancing our understanding of the mechanisms, impacts, and consequences of armed conflict on the environment. Contributions addressing environmental monitoring, attribution, post-conflict recovery, environmental governance, or implications for sustainability and climate policy are particularly encouraged.

Nature-related decisions in finance, policy and official statistics increasingly require credible, scalable and spatially explicit evidence. Yet translating Earth observation and in situ measurements into fit-for-purpose indicators remains difficult. This session connects remote sensing, ecology, environmental sciences, accounting, finance and decision-makers to examine indicator validity, uncertainty, spatial and temporal scale, methodological transparency, data provenance, and fitness for use.

We invite integrated contributions linking remote sensing or ecological methods to at least one concrete accounting, disclosure or market application. Topics include, but are not limited to, mapping and assessing ecosystem condition and services, biodiversity intactness, land use intensity, anthropogenic pressures, and water-related environmental indicators; combining Earth observation with field data and models; addressing baselines, uncertainty, scale and change; and ensuring data traceability, reproducibility, validation and auditability. Applications may include national environmental-economic accounts, including ecosystem accounts implemented under SEEA Ecosystem Accounting; TNFD-aligned reporting by companies and financial institutions; and monitoring, reporting and verification for biodiversity and nature-based carbon credits.

The session will bring together Earth observation, environmental and ecological scientist, nature accountants, policymakers, standards and assurance specialists, and financial practitioners to compare what indicator producers can robustly deliver with what users need for real decisions. We particularly welcome co-designed and operational case studies, including critical assessments of where indicators fail or are misapplied, rather than only new maps or algorithms.

Addressing today's environmental and climate-related challenges requires strong collaboration among researchers, public authorities, private companies, and local communities. This session will explore how the integration of field observations, scientific research, technological innovation, and stakeholder engagement can support more effective environmental protection and sustainable territorial development. Contributions are invited on multidisciplinary approaches that combine monitoring systems, Earth observation, environmental data, digital technologies, and decision-support tools with practical applications in risk management, climate change adaptation, ecosystem conservation, and sustainable land-use planning. Particular attention will be given to successful partnerships between academia, industry, public institutions, and civil society that facilitate knowledge transfer and the implementation of innovative solutions. The session aims to foster dialogue across disciplines and sectors, promoting the exchange of experiences, methodologies, and best practices to strengthen the resilience, sustainability, and long-term management of natural and human environments.

The session deals with scientific concepts and empirical studies in the natural and social sciences and humanities that address the societal pressures on the Earth system or the impacts of Earth system changes on societies in the context of the Anthropocene. It involves inter- and transdisciplinary approaches for a better understanding of (i) key interlinkages, feedbacks and natural and social tipping points, (ii) normative views of habitability such as planetary boundaries and social justice, and (iii) transformative capacities to preserve or regain habitability. Explicit account is taken of the complexity, dynamics and uncertainties of the underlying Earth system processes, as well as of associated social, economic and political developments across spatial and temporal scales. The aim is to explore the potential of deeper integration of the different research strands with their ontological and epistemological knowledge and empirical evidence for the advancement of Anthropocene research. Contributions can be on topics ranging from anthropogenic pressures on Earth system compartments such as climate, biodiversity, water, soil and land and/or their impacts on settlements, infrastructure, livelihood, food security and human health with secondary effects on poverty, inequality, and migration. Selected guiding questions are: What additional knowledge and methods are needed to more appropriately describe key interlinkages between the Earth system and societies shaping the Anthropocene? Are the political and social responses to this global challenge necessarily global and if not, how is decision-making and power best devolved to local levels where flexible community resilience might be fostered? What natural and social sciences and humanities’ evidence is needed as reference to further negotiate and agree on the future habitability of the planet for human societies and all wild species? What science communication and education can facilitate the transfer of actionable knowledge and strengthen societal and mental capacities for sustainability transformations without destroying the hope for a liveable future? Approaches from all related disciplines and studies from around the world will be considered. (Continuation of Session ITS3.2/SSP1.8 at EGU26 as second edition of an EGU session series)

As environmental governance undergoes a digital transformation, there is a decisive shift from static reporting toward dynamic ecosystems that facilitate real-time assessment and causal attribution. However, translating scientific insight into political action remains challenging, requiring raw data to be transformed into robust, legally defensible evidence. Recent advances in data science are expanding this capacity and offering more precise tools for impact assessment, explicit quantification of uncertainty and advances in explainability. At the same time, significant hurdles remain: The "black-box" nature of certain predictive models, the difficulty of communicating scientific uncertainty to non-experts, as well as the complexities of causal attribution in open systems must be addressed to ensure these methods are fit for purpose and lead to resilient governance.

This evolution enables a transition from reactive to proactive governance, providing the empirical rigor necessary to design and refine environmental interventions, such as water quality regulations and low-emission zones across spatio-temporal scales.

The session aims to provide a venue to present the latest progress in bridging the gap between environmental data science and policy implementation. We welcome abstracts focused on, but not limited to:

- Cross-sectoral case studies: Implementation of evidence-based governance in air quality, biodiversity, water management, or climate adaptation.
- Uncertainty quantification: Probabilistic modelling and frameworks for communicating scientific uncertainty to decision-makers.
- Interpretability and Explainability: Methods to ensure that data-driven models are transparent and legible for administrative and legal use.
- Causal inference: Causal impact assessment of policy interventions, counterfactual analysis, and the use of quasi-experimental methods.
- Evidence-based monitoring: Designing data collection networks and sensors specifically to support policy evaluation and KPIs.
- Adaptive governance: The use of real-time data streams for iterative policy adjustment and "course-correction" (feedback loops).
- Decision-support systems: The development of tools and metrics that translate scientific observations into actionable policy options.
- Institutional frameworks: Strategies for integrating data science workflows into government agency structures and legislative processes.

Geology does not only shape the physical environment in which societies develop. Rocks, landforms, geological and hydrological processes, water bodies and other abiotic features also influence how people perceive, use, interpret and culturally appropriate their surroundings. Through these interactions, geodiversity becomes embedded in cultural landscapes, local identities, traditions, beliefs, myths and other forms of tangible and intangible heritage.
Cultural geology – also developed in some scholarly traditions under the term Culture Geology – provides an interdisciplinary framework for exploring relationships between geological environments and human societies, while geomythology examines how geological phenomena, extreme events and landscape features are interpreted, remembered and transmitted through myths, legends and oral traditions. Together, these approaches reveal dimensions of geodiversity and geoheritage that may remain difficult to capture through purely geoscientific assessment.
Building on the concept of mythogenic landscapes, we invite contributions examining how abiotic features and processes act as culture-shaping factors. Geological, geomorphological and hydrological characteristics can influence myths and imaginaries, settlement patterns, sacred and monumental landscapes, cultural practices, architecture, material culture, the use of geological materials, place names, local knowledge, and perceptions of environmental change and natural hazards. Conversely, cultural interpretations may influence how geological features are valued, protected and incorporated into heritage.
Particular attention will be given to intangible geoheritage, geocultural heritage, geomythology, geofolklore, hydromythology, Indigenous and local knowledge, cultural perceptions of geological materials, geological materials in architecture and archaeological heritage, collective memory of geological processes and extreme events, toponymy, geoconservation, geoeducation, geotourism and public engagement.
We welcome studies combining geosciences with archaeology, history, anthropology, folklore studies, ethnography, cultural geography and heritage studies. The session aims to bring together geoscientists and scholars from the humanities and social sciences to develop a holistic understanding of relationships between people and the abiotic environment and of how cultural meanings contribute to the recognition, interpretation and protection of geoheritage.

In March 2024, the proposal to formalize the Anthropocene as a new geological epoch was rejected (IUGS 2024). This decision constitutes a turning point in debates on the Anthropocene that have been ongoing for more than two decades.
Initially proposed by Paul J. Crutzen in 2000, the Anthropocene was conceived as a new geological epoch dominated by human activities, marking the end of the Holocene (Crutzen and Stoermer 2000; Crutzen 2002). Since then, it has generated numerous debates across the natural and social sciences and beyond (Benner et al. 2021; Bohle et al. 2025), including opportunities to reconsider relations between humans and nature inherited from modernity (Latour 2017).
The Holocene therefore remains the geological epoch in which we officially live (IUGS 2024). Yet the transformations that gave rise to the Anthropocene debate have not disappeared. Anthropogenic global change continues, including climate change and transformations associated with the Great Acceleration (Steffen et al. 2015; Head et al. 2022). We thus continue to live geologically in the Holocene while researchers across Earth system sciences, social sciences, and the humanities investigate the Anthropocene (Thomas, Williams, and Zalasiewicz 2020; Rockström et al. 2026). Recent debates following the 2024 decision further demonstrate that the scientific discussion remains open (Waters et al. 2026; Zhou and Bertini 2026; Zalasiewicz et al. 2026; Merritts and Walter 2026).
This situation invites us to ask: What should we now do with the Anthropocene? What is the relevance of the Holocene in a time of anthropogenic global change? What kinds of interdisciplinary research can emerge from these debates?
Rather than reopening the institutional vote itself, this session provides an open space to examine geological evidence and arguments surrounding the proposed Anthropocene–Holocene boundary, their implications within and beyond geology, and new interdisciplinary horizons for the social sciences, education, philosophy, the humanities, and geoethics (Wallenhorst and Wulf 2023; Renn 2021; Bohle et al. 2025; Colombo 2026).

Mangrove ecosystems provide a series of services, such as coastal protection, carbon sequestration, and biodiversity support. Despite the growing popularity of restoration initiatives, many of them continue to show low long-term survival rates. The main cause for this is the disregard for hydrological and sedimentological constraints as well as poor monitoring protocols. This session aims to connect researchers, practitioners, policy-makers, and others to combine ecological research, engineering principles, and coastal management experience. The empirical evidence, guidelines, and practical insights have the potential to subsidize the improvement of mangrove restoration strategies.
We invite submissions addressing, but not only, the following themes: 1) case studies and lessons learned; 2) hydrology and geomorphology; 3) restoration methodologies; 4) monitoring and blue carbon accounting; and 5) socio-ecological dynamics.

Understanding and responding to Europe’s climate risks requires sustained investment in science, from fundamental research and the development of research talent to long-term observations, advanced analytical capabilities and world-class research infrastructures. Climate risks are increasingly interconnected across ecosystems, food systems, human health, infrastructure, and the economy and finance, highlighting the need for robust knowledge, data and research capabilities to understand their interactions and strengthen climate resilience.
Across the Horizon Europe programming period, Pillar I – Excellent Science has contributed to this knowledge base through frontier research supported by the European Research Council (ERC), researcher training, mobility and interdisciplinary collaboration through the Marie Skłodowska-Curie Actions (MSCA), and the development, access and integration of European Research Infrastructures (RIs).
The session welcomes contributions on how frontier science, research talent and research infrastructures provide the knowledge, data, methods and scientific capabilities needed to address these risks areas and interactions among them, including compound, cascading and cross-border risks. Research highlighting risks associated with heat, drought, floods, wildfires and changes affecting marine and terrestrial environments are particularly encouraged.
By bringing together researchers, projects and infrastructures supported across the different components of Horizon Europe Pillar I, the session aims to connect complementary expertise and capabilities and explore how Excellent Science can provide the knowledge, people, observations and research capacity needed to better understand Europe’s interconnected climate risks and strengthen the scientific foundations for a climate-resilient Europe.

Nature-based coastal solutions (NBCS), such as saltmarsh and mangrove restoration, living shorelines, beach and dune rehabilitation, and reef structures (artificial and natural), are increasingly promoted as sustainable responses to the complex challenges of coastal zone management. These approaches aim to harness natural processes to stabilise coastlines, reduce flood and erosion risk, enhance biodiversity, and provide co-benefits, including carbon storage and improved water quality. While the physical and ecological advantages of NBCS are supported by growing evidence, significant uncertainties remain about their long-term effectiveness, particularly under changing climate and socioeconomic conditions. These knowledge gaps are especially critical for informing policy and investment decisions in coastal infrastructure and adaptation strategies. We invite contributions that integrate coastal geoscience, engineering, and broader system-level thinking to evaluate the long-term performance, risks, and trade-offs of NBCS across diverse environmental and governance contexts. We encourage submissions that include, but are not limited to:

(a) case studies on NBCS implementation across varied coastal geomorphologies and hydroclimatic regimes, with evidence of long-term outcomes or monitoring data;
(b) modelling studies that assess NBCS performance under future climate and sea-level rise scenarios;
(c) innovations in field methods, remote sensing, and data integration for evaluating NBCS impacts on geomorphic and ecological processes;
(d) systems-based approaches (e.g., coupled human-natural models, scenario planning) that address feedbacks between NBCS, coastal dynamics, and socioeconomic systems;
(e) studies that focus on advancing the engineering design of NBCS and may include recommendations for types and values of design parameters and criteria;
(f) perspectives on the institutional, regulatory, and financial frameworks influencing the deployment and long-term maintenance of NBCS.

We particularly welcome interdisciplinary studies that combine geoscientific analysis with insights from ecology, engineering, planning, and policy, and encourage dialogue on how transdisciplinary approaches can help guide the design, implementation, and long-term governance of effective NBCS.

Globally, landscapes are starting to dynamically respond to human-accelerated climate change hazards. Whilst in the past it was often possible to use geotechnical solutions to control natural landscape dynamics, such as using nature-based or engineered solutions to control river morphology, reduce coastal erosion and flood risks and reduce landslide hazards, these methods are increasingly unviable. As climate change impacts accelerate there will be growing economic, social or physical limits to continued use of ever more expensive geotechnical solutions. Managing many of our landscapes using geotechnical solutions will achieve hard adaptation limits. This session welcomes papers that explore the potentialities of hard physical adaptation limits and the impacts of these for our societies which are built assuming a relatively ‘fixed’ landscape. We welcome papers that can demonstrate how many nature-based solutions work against rather than with natural landscape responses to environmental factors such as sea level rise, increased river flows (leading to avulsions), increased rainfall triggering landslides more frequently and/or drought conditions driving more widespread wildfires reducing landscape stability. Papers exploring some of the wicked problems that arise from increasingly dynamic landscapes, including release of wastes, graves and buildings into the landscape are also sought.

The growing scientific and policy focus on tipping points in the Earth system reflects their potential for profound physical and socio-economic consequences. If crossed, tipping points could trigger abrupt changes that are effectively irreversible on human timescales. Continued Global Warming is predicted to drive major changes across the North Atlantic, pushing key components of the climate system towards potential critical thresholds and abrupt reorganisation. Yet, the nonlinear nature of these systems means that future change is difficult to observe, model, predict, and govern. Early Warning Systems (EWS) have emerged as a potential method of translating our understanding of abrupt changes in the climate and their impacts into useful and actionable information for relevant stakeholders and decision makers.
Important questions remain around how best to inform and govern the response to North Atlantic tipping and what information can be robustly provided considering deep uncertainty.

To address these challenges, this session aims to bring together interdisciplinary perspectives to inform the co-design of EWS that can support tipping point governance. We welcome contributions from observations, modelling, impact studies, and governance. We have particular interest in modern approaches able to inform governance and response, including under deep uncertainty. Our primary focus is on North Atlantic tipping elements, including the Atlantic Meridional Overturning Circulation, Subpolar Gyre and Greenland Ice Sheet. Studies of other tipping elements and their interactions are also welcome. This session builds on themes being explored by the UK Advanced Research and Invention Agency (ARIA) Forecasting Tipping Points programme.

Water management in Europe has often relied on emergency response, reacting to floods, droughts and scarcity once they occur. Three recent EU policy developments mark a shift in this framing: the Nature Restoration Law (2024), the EU Water Resilience Strategy (2025), and the Competitiveness Compass 2025). Together they treat water and landscapes not only as risks to manage, but as protected natural infrastructure that contributes to ecosystem health and a sustainable economy. This session invites contributions that move beyond reactive risk management toward proactive, systemic resilience: landscapes and catchments designed to absorb shocks, restore ecological function, and generate long-term value.
We welcome studies addressing how catchments, rivers, cities, and rural landscapes can be reimagined as resilient systems considering binding restoration targets. Relevant approaches include nature-based solutions, water reuse and circularity, digital twins for landscape and catchment planning, and governance models that align water security with economic strategy.
Of particular interest are creative, cross-disciplinary approaches connecting hydrology, ecological restoration, landscape design, engineering, and policy: how can we design landscapes that are simultaneously flood-resilient, drought-resilient, ecologically restored, and economically productive?
Contributions may range from local to continental scale, and include case studies, modelling work, policy analysis, or nature-based interventions, connecting risk science, legal restoration requirements, economic sustainability, and long-term resilience planning.

Freshwater systems, societies and ecosystems are often studied separately, yet they are deeply intertwined parts of complex social-ecological systems. Advancing a holistic understanding of these systems is essential to addressing many grand challenges of the Anthropocene, such as ensuring water security, biodiversity conservation, and climate change mitigation and adaptation.

This session invites a broad range of submissions that study the dynamics of freshwater social-ecological systems. These may include socio-hydrological, ecohydrological, social-ecological, or other approaches that share an interest in investigating the properties of complex adaptive systems (eg., thresholds, resilience, emergent behaviour, path dependence, cross-scale effects).

We invite empirical, model-based, and theoretical contributions, which may include, but are not limited to:
- Network analysis, agent-based modelling, and system dynamics studies that represent feedbacks between hydrological processes and human behaviour such as decision-making and governance
- Machine learning and remote sensing applications to detect system change, map risks, and anticipate regime shifts
- Analysis or modelling of tipping points and cross-scale teleconnections (for example, virtual water trade) in human-freshwater systems
- Research on how ethics, power, justice, and values shape, and are shaped by, interactions between infrastructure, policy, and biophysical systems, including transdisciplinary work co-produced with water users, communities, and decision-makers

This session's overarching aim is to bring together diverse communities (hydrologists, ecologists, data scientists, social scientists, and sustainability scientists) into an interdisciplinary dialogue about the complex interactions between freshwater, society, and ecosystems. We especially welcome contributions showing how understanding these interactions can inform freshwater management to advance broader social and sustainability goals.

The interconnections between climate, environment, and human health are becoming increasingly apparent, as climate change poses growing threats to public welfare worldwide. Rising temperatures, more frequent and intense extreme weather events (e.g., heatwaves, floods, droughts), and environmental stressors such as air pollution, degraded ecosystems, or shifting land use patterns have direct and indirect impacts on population health. Climate-related changes also affect the distribution of vector- and waterborne diseases, contribute to the severity of wildfires, and influence mental and physical health outcomes.
Addressing these multifaceted challenges requires close collaboration between disciplines, bringing together climate scientists, epidemiologists, environmental and public health researchers, as well as social scientists. This session provides a platform for presenting recent advances in understanding and quantifying environment- and climate-related health risks through the integration of diverse data sources, including remote sensing, environmental monitoring, climatological measurements, health records, and socio-demographic information.
We welcome contributions that explore methods to assess climate-sensitive exposures (e.g., heat, air pollution, allergens), model health impacts across different temporal and spatial scales, develop risk maps, and evaluate adaptation or mitigation strategies. Approaches using machine learning, statistical modelling, scenario analysis, and other innovative tools are encouraged. Both empirical studies and methodological advances, whether focused on local, regional, or global scales, are invited. The session aims to foster cross-sectoral exchange and support the development of data-driven strategies for climate-resilient and equitable public health.

Decision-makers are increasingly required to consider extreme weather events as part of evaluating, disclosing, and responding to complex climate risks. Interdisciplinary approaches are required to properly understand these complex risks and to inform the best responses, including mitigation and adaptation approaches. In this session we examine how interdisciplinary teams across academic, industry, and government sectors are working to understand extreme weather events and their changes in a warming climate. Event types can include but are not limited to temperature, precipitation, wind, and compound extremes, and their impacts on people, the built environment, or the natural world. A specific focus will be on collaborative efforts to find and solve shared challenges across disciplines.

Topics of interest include

- physical climate science required for decision making
- early warning systems and their use in real-world scenarios
- risk management in the financial and insurance sectors
- impact-based understanding of extreme weather events
- assessment of varying hazard, exposure, and/or vulnerability
- storyline approaches to risk understanding.

Climate risk and adaptation assessments generally estimate aggregate damages, avoided impacts, or cost-effectiveness. Yet aggregate metrics mask who is exposed, who can adapt, who benefits from adaptation investments, and who bears residual, transferred, or cascading risk. This session asks how conclusions about climate risk and adaptation change when distributional outcomes, adaptive capacity and adaptation limits become explicit components of assessment and decision-making.

We invite quantitative, data-driven and mixed-method contributions representing inequality throughout the assessment chain, from hazard, exposure and vulnerability to impacts, adaptation appraisal and decision-making. Of particular interest are studies moving beyond generic exposure and vulnerability to capture differentiated and dynamic adaptive capacity linked to income, wealth, access to services and infrastructure, housing tenure, mobility, informality and demography.

A central focus is the operationalisation of equity and justice as measurable outcomes. This includes inequality in baseline climate risk (e.g. via revised exposure and vulnerability functions), the distribution of adaptation costs and benefits, inequalities created or exacerbated by adaptation itself, and limits to adaptation. We welcome work that stratifies impacts and avoided losses across population groups, embeds equity metrics in cost-benefit and multi-criteria assessment, examines non-monetised losses, or tests whether conventional welfare and efficiency metrics underrepresent particular populations. Contributions on adaptation-induced inequalities, including displacement, green gentrification, unequal infrastructure protection, and the exclusion of underreported populations, are especially welcome.

The session spans hazards, sectors and scales, including urban systems, critical infrastructure, health, accessibility, macroeconomic impacts, and loss and damage. We particularly encourage assessments of direct, indirect and cascading risks, asking who inherits risk when adaptation protects particular places, infrastructures or groups while shifting impacts elsewhere. We also welcome methodological work on data challenges in distributional risk assessment, including high-resolution socioeconomic data, Earth observation, mobility and geospatial data, citizen science, and alternative sources complementing conventional statistics.

Nature-based Solutions (NbS) are “actions to protect, conserve, restore, sustainably use and manage natural or modified ecosystems, that address socio-economic and environmental challenges, while simultaneously providing human well-being, resilience and biodiversity benefits”. Within the framework of a global ecosystem approach, NbS must encompass ecological, societal, political, economic and cultural issues at all levels, from the individual to the collective, from local to national, from the public or private sphere.

As underlined by the IPCC and IPBES, climate change and biodiversity loss are deeply interconnected and must be addressed jointly. This session therefore focuses on how NbS can serve as adaptation strategies to climate change, while simultaneously preserving or restoring biodiversity. Considering various ecosystems (marine and coastal, urban, cropland, mountainous, forest, rivers…), NbS as climate change adaptation solutions includes the adaptation to: sea level rise (flooding and erosion), changes of the water regime (floods, droughts, water quality and availability), rise in temperatures (heat waves, forest fires, drought, energy consumption), plant stress and increase of pests (variation of yields, forest dieback), to minimize their associated social and economic negative impacts.

Therefore, this session aims to promote discussion integrating multiple disciplines related to ecosystem restoration, preservation and management, to put forward the complexity that is often hidden by simplifying hypotheses and approaches (sector-based silo approach, homogeneity of environments...).

Specific topics of interest are the followings:
- Complexity: nature of ecosystems and risk of oversimplification, interconnection between NbS and complementary areas, consideration of uncertainties
- Scales: spatial scales with the integration of NbS in their environment, and temporal scales considering sustainability over time, variability of bio-physical processes and climate change effects
- Ecosystem services: bio-geophysical processes, spatial shift between the location of NbS and the beneficiaries one, modification under climate change (tipping point), co-benefits or negative effects
- Assessment and indicators: measurement and modelling protocols, capacity to measure the complexity, resilience and stability of NbS
- Co-development with stakeholders, engaging civil society, and integrating NbS into education, aligned with IAHS HELPING Decade objectives.

Several subsystems of the Earth have been suggested to possibly react abruptly at critical levels of anthropogenic forcing. Examples of such potential Tipping Elements include the Atlantic Meridional Overturning Circulation, the polar ice sheets, tropical and boreal forests, as well as the tropical monsoon systems. Interactions between the different Tipping Elements may either have stabilizing or destabilizing effects on the other subsystems, potentially leading to cascades of abrupt transitions. The critical forcing levels at which abrupt transitions occur have recently been associated with Tipping Points.

It is paramount to determine the critical forcing levels (and the associated uncertainties) beyond which the systems in question will abruptly change their state, with potentially devastating climatic, ecological, and societal impacts. For this purpose, we need to substantially enhance our understanding of the dynamics of the Tipping Elements and their interactions, on the basis of paleoclimatic evidence, present-day observations, and models spanning the entire hierarchy of complexity. Moreover, to be able to mitigate - or prepare for - potential future transitions, early warning signals have to be identified and monitored in both observations and models.

This multidisciplinary session invites contributions that address Tipping Points in the Earth system from the different perspectives of all relevant disciplines, including

- the mathematical theory of tipping points
- methods to anticipate critical transitions from data
- tipping points in climate models across the hierarchy, including comprehensive Earth system models
- climatic, ecological and socioeconomic impacts of tipping events
- decision theory in the presence of uncertain tipping point estimates and uncertain impacts

Water underpins every aspect of life, from healthy ecosystems to economic prosperity and human well-being. Climate change intensifies risks such as droughts, floods, and water quality degradation; a reality starkly evident across Europe in recent years. In this context, ensuring water resilience becomes an urgent priority. One year after the adoption of the EU Water Resilience Strategy (2025), significant efforts are needed across European regions to align governance, financing, and systemic innovation for protecting water resources and fostering a water-smart economy. Nature-based Solutions (NbS) are central to achieving these ambitions. By restoring ecosystems and their biodiversity, enhancing natural water retention, and reinforcing connectivity between terrestrial and aquatic systems, NbS offer transformative pathways to strengthen socio-economic-ecological resilience. However, moving from strategic ambition to practical and large-scale deployment has revealed complex real-world challenges. From regulatory and institutional bottlenecks to financial hurdles, social resistance, technical performance gaps, and a widespread lack of specialised technical expertise, empirical know-how, and operational capacity among solution providers, the path to mainstreaming NbS is rarely linear.
This session aims to critically examine the reality of NbS projects one year into the EU Water Resilience Strategy framework. We invite contributions from both recently initiated projects and longer-standing NbS experiences that offer valuable evidence and lessons for the Strategy. Submissions should showcase both aspects of NbS implementation: success stories on one hand, but also the concrete barriers, unexpected outcomes, failures, and trade-offs encountered along the implementation process and the strategies used to overcome them. Submissions may present real-world case studies demonstrating how institutional, social, or technical hurdles were successfully navigated through adaptive management and problem-solving. Finally, submissions showcasing long-term monitoring, measurable impacts, potential for scalability, and NbS co-benefits for water availability, disaster risk reduction, and ecosystem management are highly encouraged, ensuring that the discussion bridges scientific evidence with real-world impact to enhance water resilience.

The hazard isn't the event; the hazard is the sequence. Disaster risk is usually assessed event by event, yet many of the most damaging outcomes arise when hazards follow one another. Earthquakes alter drainage, slopes and sediment supply before the next flood or monsoon; floods weaken structures before the next earthquake; wildfires change how catchments respond to rainfall. Two examples show how one event changes the conditions under which the next unfolds. The 2015 Gorkha earthquake in Nepal was followed by increased landsliding in the monsoons that came after it. The 2023 Kahramanmaraş earthquakes in Türkiye were followed by flooding in the Asi (Orontes) catchment in 2026. Understanding such sequences means connecting physical processes to the people, buildings and institutions that experience them.

This session invites inter- and transdisciplinary contributions on sequential and cascading hazards and their consequences. Topics include field evidence and reconnaissance of hazard sequences; modelling of how earlier events change hazard, exposure and vulnerability, including damage accumulation; health, housing and indoor-environment outcomes in multi-hazard settings; governance, accountability and responsibility for multi-hazard risk; and methods for transferring lessons across hazards, regions and institutional contexts. We welcome geoscientists, engineers, public health researchers, social scientists and practitioners, and particularly encourage early-career researchers and colleagues from affected regions. The session complements multi-hazard assessment sessions in NH by bringing physical and societal perspectives on hazard sequences into one conversation.

River deltas and coastal plains are highly vital environments, offering a wide range of ecosystem services that make them hotspots of biodiversity and human settlement, and key for economic production and food security. Human activities such as river damming, resource extraction and land-use land cover change have significantly altered coastal-deltaic morphodynamics, interact with and accelerate biophysical impacts from climate change. Consequently, these low-elevation environments face increased risks of land subsidence, erosion, relative sea-level rise, flooding and salinity intrusion, all of which impact the functioning of coastal social-ecological systems. These accelerating pressures are promoting key advances in understanding the driving processes, the threats generated and the ways humans are addressing these through management. Developments have come from earth observations using remote sensing, and from modelling, increasingly supported by artificial intelligence, in addition to conceptual advances in critically analyzing the human-coastal wetland relationship from both geoscience and management perspectives, preferably interlinked. Critical research gaps persist, however, regarding all aspects of processes and geomorphic responses to these threats, and these limit our capacity to predict and manage coastal lowland and delta change. A more integrated, multi- and interdisciplinary understanding of the interacting processes and impacts is needed to manage river deltas and coastal plains in a sustainable and inclusive manner. This requires taking a system’s perspective, connecting insights from coastal geomorphology and geology, hydrology and hydrogeology, natural hazards and disaster risk science, as well as human geography and social sciences. This session provides an interdisciplinary platform that welcomes contributions that advance an integrated understanding of the emerging changes, pressures and the interconnected processes and hazards they generate; assess the implications for coping capacity and resilience; explore developments in earth observation and modelling efforts to address them; point out persisting knowledge gaps and identify opportunities for effective management and sustainable development of these coastal lowlands.

Climate change poses a significant threat to sustainability. It disproportionately affects different social groups, intensifying interconnected risks across socio-ecological systems and challenging conventional approaches to disaster risk reduction and adaptation. These challenges are particularly pronounced in climate-sensitive ecosystems, such as arid and semi-arid regions, where land degradation, water scarcity, biodiversity loss, and socio-economic vulnerability intersect.

Nature-based and community-led strategies offer effective, context-specific solutions that reduce climate risks, restore ecosystems, enhance biodiversity and ecosystem services, and support local livelihoods, enabling sustainable and equitable adaptation even in highly constrained environments such as drylands.

This session invites contributions that explore how nature-based and community-led approaches support disaster risk reduction, ecosystem restoration, and climate change adaptation across diverse ecological and socio-economic contexts, with a particular focus on research that:
- Assesses the effectiveness of these strategies in reducing risk and enhancing climate resilience
- Examines socio-ecological trade-offs and synergies by integrating ecological and social science perspectives within systems-based approaches
- Evaluates long-term resilience and restoration outcomes across varied ecological and socio-economic contexts, including arid and semi-arid landscapes
- Engages with Indigenous and local knowledge systems, emphasizing culturally grounded and community-driven solutions
- Investigates governance challenges, structural barriers, and enabling conditions, and explores inclusive frameworks that support equity, participation, and sustainability
- Investigates synergies and trade-offs between nature-based approaches and conventional measures
- Examines the effectiveness, resilience, and scalability of specific nature-based solution typologies (e.g., water harvesting, vegetation restoration, agroforestry)
- Examines innovative monitoring and assessment tools (e.g., citizen science, remote sensing, hydrological modelling, eDNA, AI) to evaluate, optimize, and scale nature-based and community-led strategies

This session is supported by the RISK-KAN Working Group on “Nature-Based and Community-Led Climate Risk Strategies.” Contributions from diverse regions are welcome, with a particular emphasis on early-career researchers and practitioners from underrepresented areas.

Cities worldwide are increasingly exposed to compound extreme weather and climate events—hazard combinations that occur concurrently, in close sequence, or across connected regions, such as heatwave–drought co-occurrence, storm surge coinciding with pluvial flooding, or extreme heat following tropical cyclones. Because their drivers interact and their impacts cascade through critical infrastructure, ecosystems, and vulnerable populations, compound events often inflict damages far exceeding the sum of individual hazards, challenging conventional single-hazard approaches to urban risk management.

This session aims to bring together researchers across climate science, hydrology, urban studies, engineering, and disaster risk reduction to advance the understanding, prediction, and governance of compound extremes in urban environments. We welcome contributions addressing, but not limited to:

1. Physical drivers and dynamics of compound events (concurrent, sequential, and spatially compounding) in a changing climate;

2. Detection, attribution, and projection of compound extremes using observations, reanalyses, climate model ensembles, and event storylines;

3. Novel analytical and modeling approaches, including statistical dependence modeling, machine learning, and AI-based methods;

4. Impacts of compound events on urban systems, including infrastructure networks, public health, energy and water security, and cascading or compounding risks;

5. Assessment and enhancement of urban resilience, including risk assessment frameworks, early warning systems, adaptation planning, nature-based solutions, and governance strategies;

6. Case studies from diverse urban contexts—including the Global South—and co-production approaches engaging stakeholders and practitioners.

We particularly encourage interdisciplinary submissions, contributions from early-career scientists, and studies that bridge the gap between hazard science and actionable resilience planning for cities.

Measuring progress in climate adaptation is essential to track resilience-building, guide investments, and inform policy. Yet, adaptation measurement remains fragmented and contested: while some frameworks focus on process indicators (e.g., planning, governance, capacity), others emphasize outputs (e.g., implemented measures), or outcomes and impacts (e.g., reduced vulnerability, enhanced resilience). Each approach has strengths and limitations, and their combination is critical to capturing the complexity of adaptation and informing adaptation action.

This session invites contributions that advance understanding and practice in measuring and evaluating progress in climate adaptation across scales, hazards and sectors. We welcome research that develops or applies frameworks, methods, and tools for adaptation monitoring, evaluation, and learning (MEL), as well as critical reflections on their usability, comparability, and policy relevance.

Topics of interest include (but are not limited to):
- Development and application of process, output, outcome, and impact indicators for adaptation, with a focus on outcomes and impacts.
- Approaches to integrating multiple indicator types for holistic assessment.
- Use of novel data sources and methods (Earth observation, citizen science, AI, participatory surveys) for MEL.
- Cross-scale measurement: from local initiatives to national reporting and global stocktake.
- Addressing uncertainty, attribution, and time horizons in adaptation measurement within the MEL process.
- Considerations of equity, justice, and governance in defining and applying adaptation metrics.
- Case studies showcasing practical experiences of tracking adaptation progress across geographies and contexts.

By bringing together conceptual, methodological, and applied perspectives, this session seeks to identify pathways towards robust, inclusive, and actionable adaptation metrics that can guide decision-making and enhance accountability under the EU Mission on Adaptation, the Paris Agreement, and other global frameworks.

The year 2026 has been marked by a sequence of destructive landslides and earthquake-triggered ground failures across different geodynamic and climatic settings, offering the opportunity to compare hazard mechanisms, early-warning performance, and civil protection responses on a global scale.
In January (16th and 25th), a destructive landslide hits the South of Italy, compromising roads, building stability, and essential services, and prompting evacuation of 1,500 people. Elsewhere, large earthquakes triggered severe secondary hazards: a Mw 7.8 quake offshore Mindanao, Philippines (8 June); a seismic doublet (Mw 7.2/7.5) in northern Venezuela (24 June) causing slope failures on steep coastal terrain; a Mw ~7.4 quake in Chocó, Colombia (10 August); and a Mw 7.7 quake off Flores, Indonesia (15 August), which blocked the Trans-Flores Highway. On 26 August, a glacier collapse in the Langtang range triggered a debris avalanche and flash flood along the Nepal–China border, destroying infrastructure and leaving over a thousand people missing.
This session aims to bring together scientists, practitioners, and civil protection agencies to discuss detection, characterization, monitoring, and response strategies applicable across these diverse contexts.
We invite contributions addressing, but not limited to:
• Remote sensing analysis (InSAR, optical/radar imagery, LiDAR, UAV) for detection, mapping, and rapid damage assessment);
• Monitoring systems and early warning, including geotechnical instrumentation and seismic detection of slope failures;
• Geomorphological characterization, including susceptibility mapping and controls on landslide reactivation;
• Civil protection and emergency response, including red-zone delimitation, evacuation planning, and cross-border coordination;
• Comparative and multi-hazard perspectives, linking seismically-induced, gravitationally-induced, and cryosphere-related slope failures, and exploring cascading hazard chains.
The session welcomes case studies, methodological advances, and policy-oriented contributions that can inform more effective cascading risks reduction strategies worldwide.

The implementation of many policies on the environment, climate, public health, and other societal challeges often involves the analysis of different scenarios for interventions or possible events. Advances in simulation methods – physical and data-driven – as well as simulation tools offer significant potential for making investigations more realistic, more accessible, or more tractable. At the same time, high-performance computing infrastructures like the EuroHPC systems allow scaling such analyses to global scales at sufficiently high resolutions. This is, for example, a key driver underpinning the European Destination Earth (DestinE) initiative, that aims to create a “digital twin” of the Earth System supporting exactly those kinds of applications in a variety of sectors.
This session explores how developments of novel applications that exploit [CV1.1]information from large-scale Earth System Models can be exploited to develop practical applications supporting policy implementation at regional and local level. Contributions are invited in the domains of climate adaptation, disaster risk management, or environmental policies, that present practical applications of interactive simulations in climate and sustainability planning. A key emphasis will be on demonstrating and quantifying the added value of tailored and/or interactive simulations for policy implementation.

Over the past few decades, landslide research has expanded considerably, producing a wealth of scientific insights. Our understanding of slope failure processes has advanced significantly, yet it remains unclear how effectively engineering geologists and geotechnical engineers focused on slope stabilization and landslide risk reduction are translating this knowledge into practice.
This session aims to bring together researchers and practitioners from diverse backgrounds to:
1. Foster collaboration and networking across disciplinary boundaries
2. Encourage the exchange of theoretical insights and practical approaches to landslide investigation and mitigation
3. Promote more efficient use of limited resources for landslide risk reduction

We particularly welcome contributions on topics such as:
• Expanding the affordable use of innovative technologies for landslide detection and mapping (e.g., optical and radar satellite remote sensing)
• Advances in subsurface characterization using customized geophysical methods (e.g., electrical resistivity, seismic tomography)
• Integration of remote sensing and ground-based data for improved landslide monitoring
• Engineering geological models as integrative tools for site-specific landslide risk mitigation
• Data availability, quality issues, and handling geological uncertainty in slope stability modeling
• Approaches to slope stability analysis, from empirical methods to advanced numerical models
• Impacts of climate variability on landslide occurrence and engineered slope performance
• Low-cost, reconnaissance-level hazard assessments in data-scarce and disaster-affected regions
• Case histories of slope stabilization and landslide mitigation, including both successful and unsuccessful interventions
• Knowledge transfer between scientists and engineers, and effective communication of landslide risk to civil protection authorities, policymakers, media, and the general public

Session sponsored by the International Association of Engineering Geology and the Environment (IAEG – https://iaeg.info)

Global initiatives such as REDD+, afforestation, reforestation, and restoration place forests at the centre of climate action. Yet these measures are highly context dependent and can create synergies and trade-offs across carbon sequestration, water availability, biodiversity, ecosystem functions, and human well-being.
Afforestation can enhance carbon sequestration, reduce erosion, regulate soil moisture, and support atmospheric moisture recycling, while in some contexts reducing streamflow, altering surface albedo, or changing groundwater recharge. Forest change can also affect evapotranspiration, precipitation recycling, and downwind water availability, highlighting the importance of green water processes and governance across spatial scales, administrative boundaries, and sectors.
The long-term effectiveness of forest-based climate action also depends on the capacity of forests as social–ecological systems to cope with, adapt to, and transform in response to disturbances and changing conditions. Compound and cascading disturbances, including drought, wildfire, heat, pests, and land-use pressures, can interact with institutional constraints and competing societal demands to undermine resilience.

This session aims to advance understanding of how forests can contribute to climate mitigation and adaptation while maintaining or strengthening social–ecological resilience under changing hydroclimatic and societal conditions. We welcome interdisciplinary studies, modelling approaches, case studies, governance analyses, and decision-support tools addressing trade-offs, compound and cascading risks, and green water governance, including:

· Social–ecological resilience, including adaptation, learning, participation, and cross-sectoral and cross-scale governance of the forest-water nexus
· Forest–water–climate interactions, including soil moisture, evapotranspiration, moisture recycling, and blue–green water linkages
· Co-benefits and trade-offs of forest-based mitigation for carbon sequestration, water availability, biodiversity, ecosystem functions, and society
· Forest disturbances, compound and cascading impacts, institutional capacity, and adaptation
· New indicators, scenarios, and decision-support approaches for resilient forest management
. Forest–green and blue water governance, including monitoring, transboundary dependencies, cross-scale coordination, and cross-sectoral decision-making.

Because they are highly interdependent, most infrastructure systems are vulnerable to disasters such as severe floods. An amazing amount of data has been made available to better anticipate the impact of severe floods and become more sustainable and resilient. Yet, integrating these data sources and modeling the impact of floods remains a challenge. Here, we develop a transferable, fact-calibrated, weakly supervised, physically constrained probabilistic modeling framework. During a flood, we estimate facility-level flood risk by integrating XGBoost and depth–damage functions. Furthermore, we leverage Granger tests, distributed-lag models, and spatiotemporal Durbin specifications to examine cross-system predictive temporal dependencies and finite-horizon lag patterns. We have three main findings. First, flood-induced damage exhibits a threshold-driven structure: damage across all infrastructure types is activated within a narrow depth band (~0.20–0.26m), suggesting universal hydraulic tipping points for sustainable infrastructure management. Second, at the predictive temporal-dependence level, cascading effects are not as extensive as their physical connections suggest. Rather than spreading everywhere, these effects are highly selective, focusing on a limited set of bridging nodes, which provides a roadmap for cost-effective resilience interventions in urban contexts. Third, resilience is shaped by the network’s propagation structure, with systematic differences in response latency and finite-horizon risk-signal persistence across infrastructure types.

Mountain regions are changing rapidly as climate warming, cryosphere loss, hydrological and ecosystem change, and socio-economic transformations interact. Looking toward 2050 provides a shared near-term horizon for asking how mountain social-ecological systems may evolve, which risks and opportunities may emerge, and how knowledge about possible futures can inform decisions today. The session addresses key and emerging themes in mountain research while remaining open to contributions from across the wider mountain research community.
A cross-cutting focus is on interactions between environmental and socio-economic change in mountain regions, including their implications for hazards, vulnerability, exposure and risk. We welcome conceptual and empirical research using observations, monitoring networks, remote sensing, models, scenarios, storylines and comparative studies to understand current trajectories and explore possible mountain futures. Contributions may address physical, ecological and societal dimensions of mountain change, from climate, cryosphere, water, ecosystems and hazards to land use, economies and governance, including mountain-lowland linkages.
We particularly encourage work that connects long-term observations with future scenarios and decision-making, investigates interactions and feedbacks between biophysical and human systems, or co-produces knowledge with communities, practitioners and decision-makers. Contributions that advance integrated approaches to monitoring, risk and adaptation, governance and the translation of knowledge into action are particularly welcome. By bringing these strands together, the session aims to clarify what different mountain futures could mean by 2050 and how choices made today may shape risks, resilience and sustainable development.
This session is endorsed and supported by the Mountain Research Initiative and the Institute for Interdisciplinary Mountain Research of the Austrian Academy of Sciences.

Earth and marine observation technologies and methods are increasingly relevant for monitoring security-related domains, including critical infrastructure and supply chains. Resilient and sustainable societies need trust. Independent observations can provide objective information that supports situational awareness, societal resilience and informed decision-making.
Monitoring critical infrastructure and supply chains can provide decision makers and security practitioners with actionable information.
Forensic investigations of specific and critical events, such as the Nord Stream pipeline incidents demonstrate how independent observations from multiple sensor technologies can help reconstruct events, assess their consequences and provide an objective scientific basis for their interpretation.
Comprehensive and objective Earth observation data can also be an effective tool for indpendent monitoring of ongoing conflicts and other security-relevant events, providing invaluable information about potential violations of international law.
This multidisciplinary session brings together research on the use of Earth and marine observations for security, resource and critical infrastructure resilience. We invitecontributions from all relevant technologies like satellite monitoring from optical or radar systems, distributed acoustic sensing (DAS), hydroacoustics, seismology and infrasound.
Contributions may address:
- novel method developments that strengthen resilience for urban areas, resources or critical infrastructure
- forensic studies of critical events
- Independent monitoring of conflicts and security-relevant events, including applications supporting transparency, verification, trust-building and peacekeeping.
- practical intersection with policy makers and Security Practitioners, i.e. how the Earth and Marine observations are disseminated to stakeholders through dedicated information sharing pipelines

This session presents key findings from the IPCC Special Report on Climate Change and Cities and invites research on the physical science basis of urban climate change and its implications for policy. Topics include two-way interactions between cities and weather and climate, urban emissions of greenhouse gases and air pollutants, urban climate hazards and risks, and the observations, models and climate services that underpin urban climate information and decision-making. Additional topics include urban adaptation and mitigation solutions, their effectiveness, challenges and prospects.

Solicited talks by report authors will highlight key findings from the assessment, followed by contributed presentations addressing its core physical science topics. We invite contributions on: interactions between cities and the climate system across scales, including urban modification of temperature, precipitation, wind and boundary layer processes; urban climate hazards and risks, including heat, flooding, water scarcity, storms and compound and cascading events under historical and future climates; the knowledge base for urban climate information, namely through observations, urban climate projections, high-resolution and city-scale modelling and climate services that support urban climate information; and how urban climate science can support decision-making across multiple levels of governance. We also welcome contributions on urban adaptation and mitigation solutions, including assessments of their effectiveness, barriers and enabling conditions, and their implications for policy.

We particularly welcome contributions from under-represented regions and works with a focus on rapidly developing and small and medium sized cities.

Socio-environmental systems are increasingly exposed to interacting environmental, climatic and societal pressures, while capacities to anticipate, respond to and transform in the face of these pressures remain highly uneven across territories. Rethinking resilience therefore requires moving beyond isolated assessments of hazards and vulnerability towards approaches that consider the interconnected dimensions of exposure, vulnerability and resilience, and their implications for action and transformation.
This session brings together research from the Belmont Forum Resilience Collaborative Research Action (CRA), "Vulnerability and Resilience Management for Socio-Environmental Systems in Exposed Territories". The seven Resilience projects engage with diverse hazards, territories and socio-environmental contexts, including floods and droughts, wildfires, coastal hazards, climate-related risks, ecosystem degradation and changing conditions of habitability. Across these contexts, they combine natural and social sciences with participatory and transdisciplinary approaches to explore how resilience is understood, assessed and strengthened.
The session will focus on cross-cutting questions emerging across this research portfolio: How are vulnerability, exposure and resilience conceptualised and assessed across different contexts? How can social, environmental and institutional dimensions be better integrated? How do local knowledge, lived experience and scientific knowledge contribute to understanding and managing risk? Under what conditions can resilience approaches support equitable adaptation and transformative pathways?
Building on the inherently interdisciplinary and transdisciplinary character of the Belmont Forum, the session will foster dialogue across disciplines, territories and knowledge communities. We particularly welcome contributions that connect environmental and social sciences, integrate different knowledge systems, engage with societal partners, and address vulnerability, exposure, resilience, governance, decision-making, adaptation and transformation.
Co-organised with the leading funding agencies ANR (France) and NSTC (Chinese Taipei), we welcome contributions beyond the Belmont Forum Resilience CRA that engage with the session's cross-cutting themes.

Nature-based Solutions (NbS) are embedded in climate-adaptation, disaster-risk-reduction, biodiversity, and water-management agendas. As climate change intensifies floods, droughts, heat, and water scarcity, NbS can strengthen water security and social, ecological, and economic resilience. Moving from promising interventions to transformative change requires credible evidence at decision-relevant scales: where, when, and for whom NbS work; how performance changes under compound hazards and future climates; how benefits and burdens are distributed; and which governance, finance, and stewardship arrangements sustain outcomes beyond pilots.
This session examines how NbS can move from isolated interventions towards interconnected portfolios and system-wide pathways for climate-resilient landscapes. We welcome inter- and transdisciplinary contributions that:
• quantify performance, uncertainty, thresholds, failure modes, and long-term change using monitoring, experiments, modeling, or Earth observation;
• improve spatial targeting, design, and adaptive management through integrated models, AI, digital twins, multi-criteria assessment, or other decision-support approaches;
• evaluate NbS portfolios and hybrid green-grey systems under floods, droughts, heat, water scarcity, erosion, and compound or cascading risks, including lifecycle cost-effectiveness across NbS, grey, and hybrid options (investment, maintenance, and replacement costs);
• assess co-benefits and trade-offs for water security, biodiversity, carbon, health, livelihoods, and infrastructure, including distributional equity and maladaptation;
• investigate multi-level and cross-sector co-creation, Indigenous and local knowledge, governance, standards, finance, procurement, maintenance, and institutional capacity for implementation and upscaling; and
• share comparative, transferability, or implementation evidence from urban, rural, riverine, coastal, and infrastructure landscapes, including underrepresented regions and negative or inconclusive findings.
We particularly encourage studies integrating at least two dimensions and connecting researchers with practitioners, communities, public authorities, finance actors, infrastructure owners, and decision-makers. Linking Earth-system knowledge with social, economic, and political perspectives, the session aims to advance pathways from individual NbS projects to effective, accountable, and durable system-wide climate and water resilience.

Mathematical models offer an imperfect and uncertain guide to future real-world climate impacts. These models (climate models, climate impact and hazard models, and catastrophe models) and their uncertainties influence how risks are understood, anticipated and managed, and therefore also play a direct role in shaping the human experience of climate risk. When informing real world decisions about climate mitigation and adaptation, the uncertainty of projections should be clearly communicated. However, open questions remain about the construction and use of these uncertainties. This includes explorations of how to navigate modelling approaches, the socio-scientific process of informing expectations of real-world outcomes and normative questions of how our uncertain expectations should inform decision making, now and in the future.

This session invites contributions from individuals and teams focused on exploring model uncertainty and decision making relating to future climate impacts, addressing topics such as:

1. Going beyond in-model uncertainty quantification (through e.g., ensemble methods, sensitivity analysis, Bayesian inference, expert judgement, scenario analysis, combining multiple lines of evidence, etc.)
2. Informing expectations of future climate impacts in the real world (e.g., escaping from model land, communicating uncertainty, social perspectives on uncertainty, storylines, etc.)
3. Informing decisions in the context of uncertainty (eg DMDU approaches, examples of co-production, ethical and responsible modelling research, integration of diverse knowledge and decision systems)

In particular, we welcome contributions which consider how modelling approaches situate themselves within a broader social context when informing decisions.

Climate policymaking and risk assessment sit at the confluence of deeply uncertain physical, social, and economic systems. Substantial uncertainty is introduced, propagated, and transformed at every stage of the climate-impact-decision chain: from projections and emulators, through sector-specific impact models, including hydrological, agricultural, and flood-loss models, to integrated assessment, energy-system, economic, financial, and insurance risk models. Yet these outputs increasingly inform decisions with long-term consequences. Understanding how uncertainty is introduced, propagated, transformed, and communicated across this chain is therefore critical for assessing the robustness of the information on which decisions are based.

This session invites contributions that advance the understanding and quantification of uncertainty across climate impacts, risk assessment, and decision-making. We welcome a range of approaches, including Monte Carlo methods, emulators, robust decision-making, sensitivity analysis, and Bayesian methods, as well as work on structural model uncertainty and inter-model comparison. We are particularly interested in studies examining how uncertainty within individual models is propagated and transformed across successive stages of an analysis, and how it can be communicated to policymakers, financial institutions, and the public in ways that support sound decision-making.

We particularly encourage submissions that bridge disciplinary boundaries among physical climate science, impact modeling, economics, decision theory, and science communication, as well as case studies examining how uncertainty is handled in real-world climate policymaking and in financial or insurance risk assessment. The session focuses primarily on analyses at regional to global scales. Sub-national case studies are also welcome when they provide insights into uncertainty relevant to broader-scale risk assessment or decision-making.

Climate projections, reanalyses and Earth observation products are increasingly available, but their spatial resolution, biases, uncertainties and limited connection to sector-specific needs often constrain their direct use in societal risk and impact assessments. At the same time, advances in artificial intelligence, statistical modelling and data integration offer new opportunities to translate climate information into actionable indicators of hazards, exposure, vulnerability and risk.
This session invites inter- and transdisciplinary contributions that connect high-resolution climate information with impacts on human health, agriculture and food systems, water resources and vulnerable populations. Relevant topics include statistical and machine-learning downscaling; integration of climate, environmental, health and socioeconomic data; satellite-derived exposure indicators; climate-sensitive health outcomes; crop and hydrological impact modelling; extreme, compound and cascading risks; vulnerability mapping; uncertainty propagation; early-warning systems; and the co-development of climate services and adaptation strategies.
We particularly welcome studies that evaluate whether climate information is fit for its intended societal application, connect methods and evidence across disciplines, compare alternative modelling or data-integration approaches, and address challenges faced by data-scarce and highly vulnerable regions. Contributions that address the needs of, collaborate with, or generate relevant information for public-health agencies, agricultural and water-management organizations, education systems, humanitarian actors, local communities and policy stakeholders are especially encouraged.

Landscapes are shaped by geomorphic processes, but life also shapes landscapes. Interactions and feedbacks between organisms, ecosystems and geomorphic processes structure many dynamic environments, including rivers, coasts, hillslopes, aeolian and deglaciating landscapes. Yet, many biogeomorphic feedbacks remain poorly understood and quantified, in particular their mechanisms, strength and thresholds. As these landscapes are increasingly affected by climate and land-use change, understanding how biota influence geomorphic processes—and vice versa—is becoming increasingly important. Improved understanding can support nature-based solutions (NbS) and geoheritage conservation and contribute to the conservation of geodiversity and biodiversity, as well as the maintenance of ecosystem functions and services.

Our session brings together research on interactions between plants, animals, ecosystem processes and geomorphic processes, landforms and materials. We particularly seek to connect researchers working in environment-specific communities, including fluvial, coastal, aeolian and hillslope geomorphology, and provide a forum to explore common biogeomorphic processes and feedbacks across environments. We welcome research spanning functional traits and individual organisms to ecosystems and landscapes, from mountain environments to the sea. By bringing together studies from different environmental settings, we aim to identify common principles, context-dependent contrasts and transferable insights in biogeomorphology, and foster synergies between research communities.

Topics may include, but are not limited to:
• biogeomorphic processes, rates and feedbacks;
• the role of plant and other organisms’ traits in geomorphic processes;
• biota as ecosystem engineers, landform creators and landscape shapers;
• biogeomorphic feedbacks under climate and land-use change;
• applications of biogeomorphology for nature-based solutions, hazard mitigation and geoheritage conservation

Innovative approaches—including field monitoring, laboratory and flume experiments, remote sensing, artificial intelligence, numerical and statistical modelling, and combinations thereof—are warmly welcomed, especially when providing new insights into interactions between life and landscape, resolving previously inaccessible interactions or pushing scalar boundaries.

Geological materials exhibit complex mechanical behaviour across a wide range of spatial and temporal scales. When polycrystalline aggregates such as glacier ice, mantle rocks, or crustal shear zones deform, their large-scale dynamics are fundamentally influenced by evolving microstructures. Processes such as crystallographic preferred orientation (CPO) development, grain-size evolution, dynamic recrystallisation, damage accumulation, phase mixing, and strain localization can strongly modify rheology, anisotropy, and deformation patterns.
Despite studying very different materials, researchers in geodynamics, tectonics, rock mechanics, and cryosphere science increasingly face the same challenge: understanding how evolving microstructure influences bulk rheology and deformation across scales, and how these effects can be represented in constitutive laws and numerical models.
This session aims to bring together researchers investigating these questions across disciplines and materials. We welcome contributions addressing the links between microstructure, rheology, and deformation, including but not limited to:
Deformation and flow across scales
Evolution of microstructure, CPO, and the anisotropy of physical properties
Rheology and constitutive laws
Strain localization, weakening and damage
Experimental, numerical, and observational constraints
Contributions from researchers at all career stages are welcome, and we especially encourage submissions led by early career scientists.
We particularly encourage contributions that bridge scales, combine multiple approaches, or foster exchange between traditionally separate research communities. We hope this session will provide a forum where ideas, methods, and modelling approaches can be exchanged across communities that do not often interact, despite facing remarkably similar questions about deformation and rheology.

Before geomaterials become “hard” rocks, they commonly pass through stages in which they behave as soft-matter systems, such as complex fluids, gels, colloids, liquid crystals, and foams. During these stages, they can be regarded as geological soft matter, which commonly occurs during lithification, crystallization and deformation. The initiation of such soft-matter behaviour is highly sensitive to the surrounding physicochemical environment, leading to the formation of striking patterns and complex structures. Understanding how these structures form and evolve remains a major challenge in the Earth sciences. Examples include soft-sediment deformation structures such as load casts and flame structures; mineral dendrites; concretions and chemical banding; crack patterns such as septaria, mud cracks and lava polygons; and dissolution–precipitation forms such as travertine dams, scallops and stalactites. Other examples include patterns associated with microbial mats, such as stromatolitic structures, together with botryoidal and spherulitic textures, as well as hydro-geomorphological patterns such as channel networks and dunes, and vegetation patterns.

The physics underlying these patterns, which evolve progressively during the soft-matter stage, commonly involves complex non-equilibrium processes governed by self-organization and self-assembly. These processes allow complex spatiotemporal patterns to emerge from simple rules, while making the underlying physicochemical mechanisms difficult to infer from the pattern alone. Exploring such physical laws and establishing a geological soft-matter paradigm would not only provide an excellent opportunity to study pattern formation itself, but also help develop analogues for understanding geological processes in Earth’s history and potentially on other planets.

In this session, we discuss the potential application of the soft-matter paradigm to geological evolution research. We invite contributions that aim to deepen our understanding of complex patterns across scales in natural and experimental systems, investigating the physicochemical processes that generate them, through field observations, experimental work, theoretical modelling, and computational simulations. Contributions involving advanced quantification, conceptual advances, quantitative model development and modelling are warmly welcome.

Rotational ground motions have emerged as an important complementary observable in
seismology, driven by advances in the development of rotational seismometers and independent
six-component measurement systems. The growing availability of these sensors is making it
increasingly possible to measure the complete six-component seismic wavefield generated not
only by earthquakes, but also by ambient and anthropogenic sources, providing new
opportunities to investigate wavefield properties and their interaction with buildings and critical
infrastructure. Sensitive to spatial gradients of the wavefield, rotational measurements carry
information that is fundamentally different from conventional translational measurements. They
therefore offer new opportunities to characterize seismic wavefields, resolve small-scale
subsurface heterogeneities, develop more complete descriptions of earthquake ground motion,
and improve our understanding of how seismic waves couple with infrastructure and contribute
to structural response and damage. Beyond traditional seismology, rotational observations are
increasingly being explored for seismic monitoring, rapid characterization of earthquake effects,
structural health monitoring, and earthquake engineering. Together, these developments open
new possibilities for integrating rotational observations across computational seismology,
geophysics, and engineering.
This interdisciplinary session brings together researchers working on the observation,
instrumentation, modelling, and application of rotational ground motions. We welcome
contributions focused on the development of rotation-measuring instruments and independent
six-component sensors; observations of earthquake- and ambient-noise-induced rotations;
theoretical and numerical modelling of rotational wavefields; full-waveform inversion;
computational seismology; seismic source and wave-propagation studies; near-field and strong
motion observations; seismic monitoring and event characterization; and applications to
structural health monitoring, earthquake engineering, and infrastructure resilience. We
particularly encourage contributions presenting new experiments and field deployments using
emerging rotational sensors, analyses of corresponding datasets, novel computational
approaches, and interdisciplinary applications of rotational ground-motion measurements.

The Antarctic continent contains approximately 10% of Earth's least understood continental crust, much of it hidden beneath the Antarctic Ice Sheet. Yet this concealed lithosphere exerts a fundamental influence on geothermal heat flow, subglacial hydrology, sediment and nutrient fluxes, ice-sheet behaviour, ocean productivity, and climate feedbacks. Understanding Antarctica therefore requires a truly interdisciplinary perspective that links solid Earth processes with the cryosphere, hydrosphere, biosphere and atmosphere. This session provides a forum for the newly approved SCAR Scientific Research Programme Antarctic Geosphere Evolution (AGE), which aims to advance understanding of Antarctica's four-dimensional lithospheric evolution and its interactions with Earth-system processes. We welcome contributions spanning geological, geophysical, geochemical, biological and modelling approaches, particularly studies that bridge traditional disciplinary boundaries. Topics may include, but are not limited to:
• Antarctic lithospheric architecture and tectonic evolution
• Geodynamics, mantle structure and geothermal heat flow
• Lithosphere-cryosphere coupling and ice-sheet dynamics
• Subglacial hydrology and groundwater systems
• Sediment, dust and nutrient fluxes from Antarctica to the Southern Ocean
• Provenance studies and reconstruction of the hidden Antarctic continent
• Interactions between geological processes, marine productivity and biogeochemical cycles
• Integration of geological, geophysical and geochemical datasets
• Integration of Antarctica’s components in full-plate reconstructions and computational tectonics.
The session particularly encourages studies that develop new connections between disciplines and improve understanding of how Antarctica's lithosphere influences the wider Earth system across spatial and temporal scales.

Essential Variables (EVs) provide a common framework for characterising key components of the Earth system, but their potential extends beyond observation and monitoring. This session explores how EV frameworks can connect heterogeneous observing systems, from Research Infrastructures (RIs) such as ICOS and ACTRIS, to satellite data and models, and support the transformation of essential observations into actionable climate information.
European Environmental Research Infrastructures (ENVRI) are a key part of this integration layer. Beyond providing observations, RIs contribute long-term stewardship, calibration and quality assurance, standards, provenance, data and access services, computational environments and increasingly integrated information services. Together with satellites and models, these capabilities provide operational foundations for connecting observations across domains and scales.
We focus on interfaces where integration remains difficult:
• EV frameworks and harmonisation: ECVs, EOVs, EBVs; definitions, metadata, provenance and harmonisation across domains, RIs and satellite data.
• Interoperability and integration: FAIR and semantic interoperability, machine-actionable data, persistent identifiers, and integration of RI, satellite, model and other environmental observations.
• Scale and uncertainty: Integration across spatial and temporal scales; uncertainty, consistency, traceability and fitness-for-purpose.
• Infrastructures enabling integration: Stewardship, quality assurance, access services, data spaces, digital twins, cloud/HPC environments, knowledge graphs and other technical and organisational architectures.
• Translation into climate services and decision support: From Analysis-Ready Data to Action-Ready Information; co-creation with users and communities; and applications in adaptation, mitigation, risk management and policy.
The session will examine the pathway from EV frameworks and European observing infrastructures to regional and local climate information, climate services and decision support. We welcome contributions demonstrating how RIs, satellite data and models can work together as an integrated infrastructure, and how this can translate observations into meaningful information for climate adaptation, mitigation, environmental management and policy support.

Archaeometry, while a broad discipline, is an important area of geoscience research, often seeking to not only utilise existing methodologies, but also pioneer new methods or approaches which often have interdisciplinary applications. Recent advances in the field across many sub-disciplines such as pigment research, conservation, paleoclimate reconstructions, mineral magnetism and dating have resulted in high-impact publications, and new insights into our understanding of the past. The interdisciplinary nature of archaeometry often means those working on novel, or interesting applications of geoscience methods can miss the opportunity to benefit from the knowledge of others working at the forefront of methods development in the field.

This session aims to bring together researchers working on novel methods or applications of methods to discuss recent advances in provenance studies, conservation, paleoclimate reconstructions and dating. We particularly welcome contributions addressing geoscience applications in pigment and materials research.

We invite contributions where geoscience methods are used to answer archaeological questions, in particular new applications, innovative approaches and novel methods are especially welcome.

The session will provide a forum to bring together those working at the forefront of their field, bringing together those bridging archaeometry and geoscience to exchange ideas, compare approaches, identify common challenges and foster new opportunities for collaborations.

We welcome contributions that address a range of environmental and societal effects of nuclear war. Areas of interest include, but are not limited to:
- Radioactive contamination
-Radioactive fallout and long-range transport
-Effects on supply chains and infrastructure
-Nuclear detonations in space and EMP attacks
-Nuclear winter and climatic disruption
-Fires and blast effects
-Smoke transport and aerosol plume dynamics
-Impacts on the hydrological cycle and oceans
-Impacts on ecological systems and ecosystem services
-The use of science to contribute to reduction of nuclear threats.

Scientific drilling, both marine and continental, provides a unique window into Earth’s interior, surface processes, paleoclimates, natural hazards and the distribution of subsurface microbial life. Past and current scientific drilling programs of the International Ocean Discovery Program (IODP), the International Ocean Drilling Programme (IODP3) and the International Continental Scientific Drilling Program (ICDP) continue to drive major advances in interdisciplinary fields of socio-economic importance, including climate and ecosystem evolution, palaeoceanography, the deep biosphere, sustainable georesources, crustal and tectonic processes, as well as geodynamics and geohazards. This session invites contributions that present or review recent scientific results from deep Earth sampling and monitoring through drilling projects. Furthermore, we welcome submissions outlining visions for future drilling projects, as well as new research emerging from scientific drilling legacy data.

The Geological Time Scale (GTS) is the result of centuries of observation, curation, and quantification of the stratigraphic record. The forthcoming iteration of the GTS, GTS2030, aims to begin the process of moving the GTS towards a broader audience, connecting domain scientists, data resources, and community organizations to develop a new modality of open science GTS construction. This session invites geochronologists, paleontologists, stratigraphers, astrochronologists, age modelers, data scientists, programmers, users of the Geologic Time Scale, anyone else interested in the next iteration of the GTS to submit an abstract. Best practices for open science, FAIR data system for the GTS are also welcome.
This session is organized by the International Subcommission on Timescale Calibration (ISTC) of the International Commission on Stratigraphy (ICS).

Plastic pollution is ubiquitous in terrestrial, freshwater, and marine ecosystems. Reliable data on plastic abundance and fluxes are crucial to study its sources, sinks, transport dynamics, and impact. Furthermore, long-term and large-scale monitoring is required to design, implement, and assess plastic pollution prevention and reduction measures. In this session we invite contributions that present recent advances in plastic pollution monitoring across the entire Geosphere (atmosphere, land surface, soil, rivers, estuaries, oceans and beyond). Presentations may focus on:
• Novel monitoring methods, including advanced techniques (e.g. remote sensing, multi/hyperspectral cameras, acoustic sensors, artificial intelligence);
• Monitoring strategies, including large-scale and long-term efforts, and citizen science approaches;
• All plastic size ranges, from nano to macro;
• Baseline studies to assess current plastic pollution levels;
• Long-term trends or recent discoveries based on plastic monitoring data.
With this session we aim to bring together scientists that work on novel approaches to provide reliable data on environmental plastic pollution.

Plastics entering natural environments immediately begin to interact with their surroundings. Rather than remaining chemically and physically inert, their surfaces are continuously transformed through physical abrasion, UV radiation, hydrolysis, oxidation, biofilm formation, adsorption of natural organic matter, eco-corona formation, and the leaching of chemical additives. These processes fundamentally modify the pristine physicochemical properties of plastics, shifting their surface chemistry, roughness, density, and buoyancy, which in turn reshapes their biological interactions and ecological impacts.
Understanding these dynamic transformations is essential because they govern how plastics interact with minerals, organic matter, microorganisms and contaminants, ultimately influencing their transport, fragmentation, persistence and ecological impacts across environmental compartments. Despite rapid progress in recent years, many of these interface processes remain poorly constrained, particularly under environmentally realistic conditions and across long temporal scales.
This session aims to bring together researchers investigating the processes that shape the plastic-environment interface across terrestrial, freshwater, marine and atmospheric environments. We welcome conceptual, laboratory, field and modelling studies that improve our understanding of how environmental exposure alters plastic properties and how these changes affect the behaviour, transport, and fate of plastics in natural systems.
We particularly encourage contributions addressing:
- Physical weathering, fragmentation, abrasion, and surface roughening of plastics
- UV weathering, hydrolysis, oxidation and other chemical transformation processes
- Biofilm development, eco-corona formation and microbial colonisation
- Interactions between plastics and minerals, sediments, natural organic matter and contaminants
- Leaching, environmental release, and toxicity of chemical additives and degradation products
- Changes in plastic properties controlling transport, fragmentation, aggregation and environmental fate
- Laboratory, field and modelling studies investigating environmentally realistic plastic alterations.
- Analytical approaches for characterising surface alteration and plastic-environment interactions
- Transport at the interface of different environmental compartments

Scientists and researchers are more and more finding new ways to present their work to a broad audience. This includes presenting data through a diverse array of visual forms, from conventional graphs and maps to interactive web applications, physical models, art installations, and other forms of tangible media. These approaches to data visualisation can make complex datasets and systems more accessible and approachable to a wider audience. Oftentimes they can reveal patterns that are difficult to see in raw data and they provide new ways of communicating scientific results to both specialised and general audiences. At the same time, the choice of which specific visual medium is used influences what can be shown, what is emphasised, and how the data are interpreted.

This session invites contributions exploring the use of physical and digital media to visualise scientific data. We welcome work that showcases data visualisation in unique ways including, but not limited to; maps, interactive visualisations, virtual and augmented environments, physical or tactile representations, and artistic approaches. Contributions may focus on the development of new techniques, the application of existing approaches to scientific problems or data, or reflections on how different visual forms affect the interpretation and communication of scientific data and research.
We particularly encourage contributions that consider the relationship between the data, the medium through which they are presented, and the people using or experiencing the visualisation. Examples from all scientific disciplines supported by EGU are welcome, as are approaches that cross the boundaries between scientific visualisation, design, art, and public engagement. And we particularly encourage contributions from underrepresented groups and countries.

A surprising visual can make us pause, notice a pattern, or ask a question we had never considered. How can we bring that potential into the way we explore and communicate data?

This session invites creative, unconventional, still-in-the-works, and carefully crafted approaches to data visualisation. We are interested in work that combines imagination with clarity: visuals that reveal relationships, communicate uncertainty, tell compelling stories, and invite audiences to explore. Contributions may address scientific discovery, education, public engagement, or decision-making at the interface of environment and society.

We welcome experiments with visual storytelling, animation, interactive exploration, hand-drawn graphics, physical data objects, immersive experiences, and combinations of visualisation with sound or touch. How can familiar datasets take unfamiliar forms? When does playful design deepen understanding? How can we make complex information accessible while preserving its nuance?

Scientists, designers, artists, educators, and communicators are invited to share methods, examples, collaborations, and lessons from experiments (including those that did not work as expected). We aim to inspire new ways of seeing data and offer practical ideas participants can bring into their own research and communication.

Art makes use of materials of geological origin: stones, pigments, mortars, metals, etc.; geology, in turn, has been depicted in various ways in art throughout art history; geosciences present their observations and discoveries in a visual form that can be regarded as an artistic expression. The entanglements of art and natural sciences are multiple, bidirectional, and have given rise to hybrid fields of research: Technical Art History, considering the materiality of artworks; archaeometry exploiting the intrinsic information contained in the artistic matter to trace back its origin and fates; Eco-critical art history, which draws on the environmental dimension of works of art – such as historical landscape painting – to critically explore the history of the environment and its changes.
In this session, we aim for a rich and diverse transdisciplinary dialogue of colleagues with multiple backgrounds and thus welcome a broad range of contributions in fields such as:
- Geosciences in artistic representation, e.g. as sources to study environmental changes, as indicators of the evolution of symbolic and scientific perception of geological objects and phenomena, natural hazards, etc.
- Artwork materials and their transformations over time as physical/chemical repositories or archives of environmental history, including air, water and soil pollution (e.g. stone degradation in urban areas)
- Geomaterials (stone, pigments, metals, precious stones) used in works of art (sculptures, metal objects, paintings, jewellery, etc.) and their intrinsic properties as an indicator of provenance or as a criterion of authenticity; the conservation issues specific to these materials.
- Artistic production and networks in geological landscapes with indigenous/local artistic use of geomaterials, artist migration to geo-resource-rich regions, transport of geomaterials to artistic centres, artistic geomaterials as indicators of power and prestige…

Climate change, biodiversity loss, pollution, natural hazards and other forms of environmental change present challenges not only for understanding Earth systems, but also for how environmental knowledge is produced, interpreted and shared. Across the Earth and environmental sciences, researchers are increasingly collaborating with artists and creative practitioners to develop new ways of engaging with environmental processes, data, places and communities.

Art-science collaboration can extend beyond communicating completed scientific findings. Creative practices may contribute to observation and sensing, working with environmental data, visualisation and representation, field-based inquiry, interpretation of uncertainty and change, participatory research, and engagement with place-based and experiential knowledge. At the same time, a growing range of projects provides practical experience of how such collaborations work in different research and environmental contexts.

This session brings together empirical case studies, methodological contributions and critical reflections on art-science collaboration in Earth and environmental research. We welcome contributions from across the geosciences and environmental sciences, together with collaborating artists, creative practitioners, and humanities and social science researchers, particularly addressing:

(1) art-science collaborations concerning climate, water, biodiversity and ecosystems, pollution, landscapes, natural hazards and other Earth and environmental processes;

(2) creative and arts-based approaches to environmental observation, fieldwork, sensing, mapping, visualisation, sonification, environmental data, modelling and interpretation;

(3) methods combining scientific observations and evidence with local, Indigenous, experiential or other forms of knowledge;

(4) participatory and place-based approaches involving scientists, artists, communities and other partners;

(5) methodological and comparative studies examining how creative practices can be integrated into different stages of Earth and environmental research;

(6) different models of collaboration, including artist residencies, field-based collaborations, museums and cultural institutions, research programmes, laboratories and community partnerships.

Despite unprecedented scientific understanding of the environmental system, translating environmental science knowledge into sustained societal action remains a major challenge. More than a decade after Stoknes (2014) described this as a psychological paradox, ecological crises are intensifying while environmental protection continues to compete with other societal priorities. Science communication research has shown that communicating more scientific facts, more clearly or more frequently, is not sufficient on its own.
Environmental science communication is consequently undergoing experimentation and transformation. Alongside established approaches, researchers are exploring storytelling, emotions, humor, aesthetics, identities, popular culture, participatory practices and novel visual formats. Digital platforms have accelerated these developments, creating spaces where scientific knowledge intersects with internet culture, entertainment, influencer practices and vernacular communication. Innovative approaches are also emerging beyond social media, including through museums, art-science initiatives, journalism and innovative institutional communication.
These developments raise questions about how environmental science communication is changing. How are communicators adapting to changing media environments and audiences? Which actors and practices are driving innovation? How are emotions, identities, aesthetics, humour and storytelling incorporated into environmental communication, and how do these approaches interact with traditional information-centred models? How are scientific institutions and researchers responding?
This session invites contributions studying and engaging with emerging forms of environmental science communication. We particularly welcome interdisciplinary research connecting environmental science with communication studies, social sciences, humanities, arts and design.

Topics may include:
• novel approaches to communicating environmental science;
• emotions, identities, aesthetics, storytelling and humor;
• visual, creative and artistic approaches;
• social media, short-form video and influencers;
• popular culture, memes and entertainment;
• participatory approaches;
• communication targeting younger audiences;
• institutional responses to changing communication environments;
• critical perspectives on the ethics and power relations of environmental communication;